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Agent Skills in category: Uncategorized

82570 skills match this category. Browse curated collections and explore related Agent Skills.

rank-by-user-fit

Scores and ranks substacker Trend Scout annotated candidates against voice-profile and goals, producing a top-10 keep list and an explicit drop list with reasons. Weighted-sum scoring across intuition-density fit, goal alignment, dedup penalty, source reliability, freshness. Produces the digest's keeps and drops sections. Use after cross-ref-topic-ledger. Trigger keywords — rank, fit score, user fit, keep list, drop list, signal weight.

lyndonkl
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16024

readability-check

Scores prose with Flesch Reading Ease, Flesch-Kincaid Grade, SMOG, Gunning Fog, and Dale-Chall, reports every score on one shared grade-band scale, and rewrites the sentences that fail. Runs on markdown files or on piped draft text before it is sent, and can run automatically through Claude Code hooks. Use before delivering any substantial written output, when a draft reads as convoluted or bloated, when a document must hit a reading-level target, or when checking a folder of documents for prose quality. Trigger keywords — readability, reading level, Flesch, Flesch-Kincaid, SMOG, Gunning Fog, Dale-Chall, grade level, hard to read, convoluted, dense prose, plain language, reading ease.

lyndonkl
lyndonkl
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reader-first-prose

Rewrites expository prose for a reader meeting the subject for the first time, not an insider who already shares the writer's knowledge. Enforces introduce-before-use (every entity, term and acronym defined on first mention, in an order a newcomer can follow), grounds or cuts every metaphor in the same breath it appears, converts compressed or nominalized logic into a plain if-then, and kills the two loudest machine tells, the em dash and the terse two-beat antithesis ("X. Not Y."). Carries an honesty pass so the prose never out-claims its evidence, marking inference as inference and preserving every number exactly. Use when a draft assumes knowledge the reader lacks, reads as insider or "clever", name-drops terms before defining them, leans on unexplained metaphor, or sounds AI-written; or when the user mentions first-time reader, plain language, define before use, sounds like AI, em dash, too clever, or jargon. Complements ladder-of-abstraction, slop-detector and narrative-fidelity-audit.

lyndonkl
lyndonkl
16024

recommend-prune

Recommends structural cleanups for the substacker section map — sections to retire, sections to merge, posts to reassign. Applies under-filled, stale, and overlapping heuristics. Writes proposals with reasons-to-reject (steelman counter). Does not execute. Use once per Curator run, after drift audit. Trigger keywords — prune, retire section, merge sections, reassign post, cleanup.

lyndonkl
lyndonkl
16024

recurring-charge-detector

Identifies recurring charges (subscriptions, monthly bills, biweekly paychecks) from a transaction history by clustering same-merchant transactions of similar amount on a regular cadence, requiring at least 3 confirming occurrences before promoting a candidate to active status. Detects new recurring charges, dormant subscriptions (missed expected dates), and amount drift, and computes annualized cost. Use when auditing subscriptions, building a recurring bills calendar, computing cash-flow forecast inputs, or when user mentions subscription audit, recurring detection, dormant subscription, or annualized cost.

lyndonkl
lyndonkl
16024

relative-valuation-toolkit

Prices a company against peers and the market with multiples — builds PE, PEG, PBV, EV/EBITDA, EV/EBIT, EV/Sales and EV/Invested Capital with the numerator/denominator consistency rule enforced, computes peer medians and quartiles, fits an ordinary-least-squares regression of a multiple on its companion variables for a sector or the whole market, reports predicted versus actual under and over valuation, and derives the intrinsic multiple from DCF fundamentals. Prices a conglomerate division by division with a sum of the parts, and values cross-holdings and minority interests. Bundles Damodaran's regional pricing regressions and multiple distributions. Use for relative valuation, comparable company analysis, trading comps, sector or market multiple regressions, justified multiples, PEG screens, sum-of-the-parts or break-up analysis, conglomerate discounts, cross-holdings and minority interests, or when asked whether a stock is cheap on its multiple.

lyndonkl
lyndonkl
16024

scene-construction-scam

Builds scenes that are reported rather than generated, by running a four-slot SCAM qualification gate (Setting, Character, Action, Meaning) with a source required per slot, a scene floor and ceiling, the 1-of-20 telling-detail cut with a provenance veto, the RUE pass, and a scene/summary narrative-distance audit against per-form ratio targets. Every technique has a person variant and a system variant (market, protocol, institution, codebase, supply chain). Use when turning research notes into a scene, opening a section with a moment, deciding whether a passage is a scene or summary, or auditing whether a vivid paragraph is actually sourced, or when user mentions scene, SCAM, show don't tell, telling detail, scene vs summary, summary in costume, establishing shot, make this vivid, or in medias res.

lyndonkl
lyndonkl
16024

score-intuition-density

Computes a 0-10 intuition-density score for a seed body using 8 concrete measurable signals — analogy presence, concrete worked example, counterfactual offered, reframe against default, biology-to-AI transfer, question posed, calibrated hedge, math-to-metaphor handoff. Emits both the numeric score and the list of triggered signals for auditability. Use after topic tagging to enrich seed frontmatter in the substacker Librarian pipeline. Trigger keywords — intuition density, score, signals, analogy count, worked example, density proxy.

lyndonkl
lyndonkl
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search-corpus

Answers "what have I already thought about X?" by searching the substacker corpus (seeds, drafts, published) for seeds matching a topic, keyword, analogy, or author. Returns a ranked list of seeds with id, title, status, density score, and a one-line excerpt. Use when another agent (Intuition Builder, Editor) needs prior thinking before generating new material, or when the writer asks "have I written about X." Trigger keywords — search, find, what have I, already thought, prior work, precedent, have I written about.

lyndonkl
lyndonkl
16024

section-break-check

Verifies the section-break style in a substacker draft matches the post register — asterisks (* * *) for essayistic posts under 2500 words, H2 for methodology / how-to / technical posts. Flags mixed registers (H2 in a reflective essay, asterisks in a structured how-to). Per the style-guide rhythm rule. Use every draft. Trigger keywords — section break, asterisk, H2, headers, register, essayistic vs methodology.

lyndonkl
lyndonkl
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section-portfolio-assessment

Classifies each substacker section as healthy / drifting / candidate-for-prune based on post volume, engagement trend, and niche alignment. Produces table + 2-4 paragraph narrative. Used in every quarterly review. Trigger keywords — portfolio, section health, healthy drifting prune, section assessment, which section is carrying.

lyndonkl
lyndonkl
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skill-construction

Methodology for building a properly structured Claude Code skill (SKILL.md + optional resources + evaluation rubric) from extracted components. Assesses complexity (Level 1 simple - SKILL.md only; Level 2 moderate - SKILL.md plus 1-3 resources; Level 3 complex - SKILL.md plus 4-8 resources), plans the resource grouping, drafts SKILL.md following Anthropic's authoring best practices (concise frontmatter with what + when triggers, body under 500 lines, progressive disclosure to resource files one level deep, workflow checklists), and constructs an evaluation rubric. Use when extracted components and a synthesis verdict are in hand and the next step is to materialize them as a skill. Trigger keywords - construct skill, build SKILL.md, skill construction, skill scaffolding, generate skill files.

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slop-detector

Scans a substacker draft for 10 signatures of AI-generated explainer slop — meta-framing openers ("In this post"), list-heavy argument, nominalization clusters, generic examples lacking first-person texture, prompt-residue phrases ("Let's break this down"), buzzword stuffing, outline-shaped paragraphs, hedge clusters, flattened uncertainty. Use when a draft "feels generic" even after voice-check passes. Trigger keywords — slop, AI-written, generic, template, meta-framing, zombie nouns, prompt residue, outline-shaped.

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special-situation-models

Values companies the standard DCF cannot handle, across five branches — distress (failure probability from a bond price or rating, blended with the distress-sale outcome), financial service firms (equity excess return and FCFE against regulatory capital, since a bank gets no FCFF and no optimal debt ratio), private companies (total beta for an undiversified owner, Silber and bid-ask illiquidity discounts), cyclical and commodity firms (mid-cycle normalized earnings), and young negative-earnings firms (a revenue and margin path plus survival odds, emitted as a dcf-valuation-engine payload). Also walks a private owner's value to an IPO offer price line by line. Use when valuing a bank, insurer, startup, distressed firm, private business, miner or deep cyclical, when pricing an IPO or a sale to a public buyer, or when asked about probability of distress, total beta, illiquidity discount, excess return models, normalized earnings, or negative-earnings valuation.

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spoken-draft-cleanup

Turns a raw dictation transcript into a clean, editable draft while preserving the writer's voice and form exactly. MECHANICAL ONLY — removes fillers and false starts, restores sentence-boundary punctuation and paragraph breaks, and FLAGS likely transcription errors as questions rather than silently fixing them. It does NOT restructure, restyle, reword, or improve. Produces the cleaned draft plus a cleanup log of every change and every flag. This is the strict intake bridge from "speak out my article" to an editable draft, run before the advisory-edit passes. Use when cleaning a dictation/voice transcript, prepping a spoken draft for editing, or doing transcript intake. Trigger keywords — clean up transcript, dictation cleanup, spoken draft, transcript intake, remove fillers, flag transcription errors.

lyndonkl
lyndonkl
16024

statement-reconciler

Verifies that an extracted statement is internally consistent by checking that opening_balance + sum(transactions) = closing_balance within a small tolerance, and produces a reconciliation report flagging missing rows, double-counted rows, sign errors, and rounding diffs. Use as the gate between PDF extraction and committing transactions to the data store, when reconciling a statement that does not balance, or when user mentions reconcile, balance check, or statement does not tie out.

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strategist-voice

Provides the house style for analyst-grade strategist writing — third-person register with sparing first-person, no em dashes, no "not X, not Y, not Z" negation cascades, numbered footnote citations rather than inline source parentheticals, specific opinion-signaling phrases, and topic-forward paragraph structure modeled on voice patterns observed in Damodaran's Musings on Markets and Thompson's Stratechery. Use when consolidating working notes into a finished long-form strategist or analyst report that must read as written by a senior human analyst rather than an AI assistant.

lyndonkl
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stress-test-analogy

Stress-tests a proposed analogy by finding the edge where the mapping breaks, then frames that break as a teaching opportunity the writer can fold into the post. Every analogy has a boundary; the writer's style treats that boundary as a feature. Use after generate-analogy-set and map-analogy-to-concept, for each framing. Trigger keywords — where does it break, stress-test, boundary, edge case, fold the break, analogy limits.

lyndonkl
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structural-analysis

Domain-neutral methodology for the second level of Adler-style reading - understanding what a document is about *as a whole* and how its parts relate. Classifies content (practical vs theoretical; sequential / categorical / structured / hybrid), states unity in one sentence, enumerates major parts and their organization, and defines the problems the document tries to solve. Reusable across any extraction workflow - skill creation from a methodology document, Pass-2 content grasp on an academic paper, structural review of a long-form document. Use when an agent has done inspectional reading and now needs to map structure before deeper component extraction. Trigger keywords - structural analysis, document structure, state unity, enumerate parts, Adler Level 2, content classification, define problems.

lyndonkl
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structural-review

Performs pass-1 structural review of a substacker essay draft — argument flow, out-of-order moves, buried topic sentences, missing pivots, weak signposting, paragraph-logic issues. Emits the "Argument flow" and "Structural blockers" sections of the Editor artifact. Use when reviewing a draft's macro-structure before addressing voice, when a draft feels like it meanders, or when the user asks whether the argument lands. Trigger keywords — structure, argument flow, outline, signposting, meandering, pivot, macro edit, substantive edit.

lyndonkl
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substack-note-rewrite

Rewrites a published substacker essay as a Substack Note using the extracted spine and chosen hook. Closest voice to the essay. Bolded maxim closer. Single link line. 60-180 words. Emits substack-note.md in the post's distribution folder. Use as the Substack-native arm of the Distribution Translator. Trigger keywords — Substack Note, note rewrite, note post, tease, Notes feed.

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summarize-signal

Given a candidate item from the substacker Trend Scout fetch, WebFetches the full post or arXiv abstract and produces a one-line "teaches X" summary plus signal_type classification (mechanism / empirical / tool / opinion / announcement / benchmark). Distinguishes teaching-content from capability-announcement explicitly. Use during the weekly run, after fetching and before ranking. Trigger keywords — summarize, signal type, mechanism vs announcement, teaching content.

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sweep-stale-seeds

Identifies substacker seeds older than 30 days with status=seed and no incoming related_seeds links, flags them for writer review, and recommends keep / promote-to-draft / kill based on density score. Does NOT auto-execute any action. Emits a review list to ops/librarian/YYYY-MM-DD-stale-sweep.md. Run at session start after ingest, once per day max. Trigger keywords — stale, sweep, review, old seeds, cleanup, gardener, corpus hygiene.

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synthesis-application

Domain-neutral methodology for evaluating completeness and logical soundness of an extracted set of components, then transforming them into actionable guidance. Runs the "is it true / is it complete / what of it" critical evaluation pass before any final artifact is built. Checks for completeness gaps, logical consistency, contradictions, and practical applicability. Reusable across any extraction workflow - skill creation (evaluating extracted components before building SKILL.md), paper extraction (evaluating Pass 2 extraction notes before deep reading), report writing (evaluating gathered evidence before synthesis). Use when an agent has extracted structured components from a source and needs to gate-check before downstream commitment. Trigger keywords - synthesis evaluation, completeness check, logic check, critical evaluation, fact-check before synthesis, gap analysis, what is not said.

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systemic-protagonist

Renders a market, protocol, institution, codebase, supply chain, disease, or ecosystem as a legible protagonist without faking agency. Builds the POSIWID character sheet (revealed objective function vs. stated purpose), the agency ledger of verb repairs, the gateway-proxy admission test, the traveling-object device, the instrumented threshold scene, and climax by constraint violation. Use when the subject of a piece is a system rather than a person, when a draft says "the market decided" or "the industry learned", when analysis reads as a data dump with no protagonist, or when user mentions systemic narrative, system as character, POSIWID, anthropomorphism, agency laundering, follow the flow, or institution as protagonist.

lyndonkl
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tag-by-topic

Assigns 1-4 topic tags to a seed body from the controlled vocabulary in substacker shared-context/topic-ledger.md. Prevents tag sprawl at small-corpus scale by requiring existing-tag match or logged addition. Uses keyword + title match; logs near-miss candidates to pending-tags. Use after format normalization and before dedupe. Trigger keywords — tag, topics, categorize, classify, taxonomy, controlled vocabulary, topic ledger.

lyndonkl
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tax-loss-harvest-scanner

Scans a taxable brokerage account for individual lots with unrealized losses above a configurable threshold, identifies wash-sale risks by checking recent buys and forward planned buys of substantially identical securities (across all household accounts including spousal), and proposes harvest pairs (sell-for-loss + immediate buy of a similar-but-not-identical replacement). Use for year-end tax planning, monthly TLH scans, after market drawdowns, or when user mentions tax-loss harvesting, TLH, wash sale, or harvest candidates.

lyndonkl
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term-interrogation

Walks a finished document line by line, finds every word and phrase standing in for a concept, and breaks each one down until a reader with no background can follow it. Targets the assumed-knowledge phrase, the kind that sounds ordinary while hiding everything that matters ("moat", "flywheel", "product-market fit", "at scale"), not merely the rare word. Explains each term where it is used, then re-reads its own explanation and unpacks any new term that explanation introduced, repeating until every word bottoms out in ordinary language. Produces a term ledger recording what was flagged, how it was handled, where each explanation came from, and how many passes it took. Use after drafting any report, explainer or analysis for a non-expert audience, or when asked to explain something from first principles, assume the reader knows nothing, cross-question the jargon, define every term, or make a document readable by a beginner.

lyndonkl
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transaction-categorizer

Assigns a category and subcategory to a financial transaction by matching its raw description against a configurable taxonomy and rules table, falling back to LLM inference when no rule matches. Emits a normalized merchant name, category path, recurring flag, and confidence score, and proposes new rules from confirmed classifications. Use when categorizing bank, credit-card, or brokerage transactions, building or refining a category taxonomy, or when user mentions transaction categorization, merchant normalization, expense classification, or category rules.

lyndonkl
lyndonkl
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transaction-deduplicator

Detects and removes duplicate transactions across overlapping bank, credit-card, and brokerage statement imports using a stable composite key (account_id, date ±1d, amount_cents, description_normalized). Emits a list of new transactions to commit, a list of suppressed duplicates with their reasons, and a list of suspicious near-duplicates that need human review. Use when ingesting financial statements that may overlap prior drops, merging multiple export sources for the same account, or when user mentions duplicate transactions, deduping a transaction file, or reconciling overlapping statements.

lyndonkl
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update-analogy-catalog

Appends an entry to substacker shared-context/analogy-catalog.md when the writer PUBLISHES a post that uses a new analogy. Not invoked on seed or draft — only on publish. Records source, target, post, freshness, mapping, where-it-breaks, and why-it-worked. Prevents silent recycling in future Intuition Builder runs. Use at publish time for any post that contains a non-trivial analogy. Trigger keywords — catalog, analogy catalog, update catalog, publish, analogy archive.

lyndonkl
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update-audience-notes

Appends one structured YAML observation block to substacker shared-context/audience-notes.md iff the week produced at least one observation with confidence ≥ medium. Includes supporting evidence (post slugs + numbers) and reviewed_by_curator flag. Never rewrites or deletes prior entries. Append-only discipline protects downstream agents' shared context. Use at the end of each weekly pipeline after write-weekly-report. Trigger keywords — audience notes, append observation, audience insight, confidence-rated.

lyndonkl
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update-section-map

Writes the canonical substacker shared-context/section-map.md after writer confirmation of review-artifact proposals. Atomic write with backup snapshot. Validates schema before writing. Use as the final step of a Curator run, only after writer has accepted/modified proposals. Trigger keywords — update section map, write section map, commit sections, apply changes.

lyndonkl
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update-topic-ledger

Maintains substacker shared-context/topic-ledger.md as an append-and-update index of all topics in the corpus. Each topic row tracks seed/draft/published counts, last-touched date, top-3 seed ids by density, and a hot/warm/cold temperature indicator. Use after any seed is created, promoted to draft, published, or killed. Trigger keywords — ledger, topic index, update index, topic ledger, hot/cold topics.

lyndonkl
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update-watchlist

Proposes adds and removes to the Trend Scout watchlist based on consecutive-failure sources, repeated-reference external authors, and user-added feedback markers. Emits a proposed diff at ops/trend-scout/watchlist-proposed-diff.md for user review. On explicit approval, applies the diff. Monthly cadence. Trigger keywords — watchlist update, add source, remove source, watchlist review, monthly review, source pruning.

lyndonkl
lyndonkl
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valuation-consistency-checks

Checks a finished valuation for internal consistency across its artifacts — currency agreement between cash flows and discount rate, terminal growth against the riskfree ceiling, reinvestment that pays for the growth assumed, perpetual excess returns, capital weights and beta range, equity bridge arithmetic, tax rates, and the hard constraints a company's type imposes. Grades each finding ERROR, WARN or INFO and exits 1 on any error, so it can gate a pipeline. Use before accepting a DCF, when reviewing someone else's model, when a value looks too high, or when checking terminal value assumptions, growth-versus-reinvestment consistency, currency consistency, or an equity bridge that does not tie.

lyndonkl
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valuation-red-team

Attacks a finished valuation the way a skeptical reviewer would — hunts bias and verdict-first reasoning, checks that each risk is charged exactly once, tests whether growth is paid for, interrogates terminal value, reverse-engineers what the market price already assumes, and applies the seven deadly sins of acquisition analysis. Use when reviewing a completed valuation, red-teaming or challenging assumptions before acting on a number, auditing a DCF someone else built, or checking double counting, control premiums, synergy claims, comparable sets and route constraints.

lyndonkl
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valuation-reporting

Assembles a finished company analysis into the deliverable a decision-maker reads — the executive summary, the value bridge, the assumptions that matter, the sensitivity range, and the recommendation with its catalysts and risks. Use when writing up a valuation, DCF, acquisition, IPO, restructuring or corporate finance analysis, when drafting REPORT.md or the verdict, or when deciding what belongs in the report.

lyndonkl
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variance-strategy-selector

Given a current win probability and a downside asymmetry flag, recommends a variance-seeking, neutral, or variance-minimizing posture and emits a numeric multiplier (typically 0.8-1.3) for downstream consumers to apply to boom-bust scores, position sizes, or bet sizes. Favorites minimize variance; underdogs maximize it. Reusable across fantasy sports lineup construction, portfolio allocation, poker bankroll decisions, racing strategy, and any decision where the agent controls a variance knob. Use when user mentions variance strategy, underdog variance, variance seeking, variance minimizing, risk posture, boom bust, must-win variance, favorite strategy, or when a decision module needs a single scalar to bias toward or away from high-variance options.

lyndonkl
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voice-check

Scans a substacker draft line-by-line against the canonical voice-profile.md don't-list and signature moves. Emits phrase-level flags with location, quoted phrase, violation type, voice-profile citation, and up-to-2 suggested rewrites per flag. Use as pass-2 skill (voice) after structural-review completes, when a draft reads competent but not in the writer's voice, or when the writer asks "does this sound like me?" Trigger keywords — voice check, delve, unpack, paradigm shift, sounds AI, does this sound like me, voice violation.

lyndonkl
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voice-fitness-check

Ranks a proposed set of framings against the writer's voice profile, especially the analogy-direction priority — biology > organizational > sports, with physics/military as voice violations. Produces a tier rating per framing and flags any framing that would break voice. Use in the Intuition Builder pipeline after generating framings, to order them by fit with the writer's register. Trigger keywords — voice fit, analogy direction, biology to AI, organizational to multi-agent, sports to calibration.

lyndonkl
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wc-archetype-mutation

The mutation operator for the FIFA World Cup Fantasy evolution engine. Applies small, bounded, feasibility-preserving perturbations to a recombined offspring squad/plan — swap one differential for an adjacent-price alternative, reorder the bench by kickoff, shift one captain-ladder step, try one fixture-swing transfer, nudge one enabler. Mutation rate is low by default and raised on demand by the diversity governor when the population has collapsed. Each mutation stays inside budget/nation/formation feasibility. Use in the mutate stage after recombination, or when wc-population-diversity calls for more exploration.

lyndonkl
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wc-building-block-crossover

The recombination operator for the FIFA World Cup Fantasy evolution engine. Crosses elite candidate squads/plans at BUILDING-BLOCK boundaries (Captain Core, Clean-Sheet Spine, Mid-Engine, Differential Pod, Enabler Bench; or for matchday plans the XI/captain-ladder/bench/sub/chip blocks) — harvesting the strongest module from each parent rather than swapping individual players — then runs a feasibility REPAIR operator (budget, nation cap, formation, 15-man shape) that restores legality from the cheapest block first and never guts a value-bearing block. Records block lineage (which parent each block came from). Implements the Evolution document's central lesson that naive crossover destroys good building blocks. Use in the recombine stage after fitness selection.

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wc-captain-ladder

Computes the optimal rolling-captaincy LADDER across a matchday's staggered kickoff sequence — the ordered captain candidates, the explicit bank-or-switch rules at each kickoff, and the captaincy_uplift that wc-fitness-eval folds into raw_xEV. Because the armband doubles the round's points AND can be MOVED during the round to a player who has not yet kicked off, captaincy EV is the expected value of the best outcome reachable by switching across the sequence — not a naive 2x of the top xEV player. Call from wc-matchday-tactician (to write MB2 of the matchday plan), from the strategists (to value a candidate's captaincy when building a matchday plan), and from wc-fitness-eval (which consumes captaincy_uplift). Returns the ladder, the switch thresholds, and the uplift against a stated baseline; the ladder is moot under the Maximum Captain chip (value = max of candidates).

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wc-chip-timing

Scores the deployment leverage of all five FIFA World Cup Fantasy boosters (Wildcard, 12th Man, Maximum Captain, Clean Sheet Shield, Qualification Booster) across the remaining tournament horizon — computing, for each chip and each candidate round, the EXTRA expected points the chip yields in that round versus an average round, then turning the leverage surface into a fire/hold call per chip this round plus a maintained earmark table (chip -> earmarked round -> trigger -> fallback). This is the math engine behind wc-chip-strategist. Reads the round's player-ev, clean-sheet, fixture/progression, ownership and captain-ladder signals plus tournament-state (chips remaining, phase, surviving nations); never re-derives them. Enforces the golden rule — never reach the semis with chips unused. Use whenever a chip decision is live (the chip-check prompt, the group->KO transition, or any round where a chip is earmarked or leverage spikes). Emits a chip-plan signal.

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wc-clean-sheet-model

Computes clean-sheet probability and defensive-returns EV for a team in a specific fixture from team defensive strength (xGA) against opponent attacking strength (xG), then models the STACK CORRELATION that turns a Clean-Sheet Spine (BB2) — GK + k same-team defenders — into a single correlated bet rather than k independent draws. Returns p_cs(team,fixture), a stack_corr_bonus capturing the amplified joint ceiling and shared downside (sign interacts with the rank objective θ — amplify when chasing, discount when protecting), and expected_ga with its conceding-points downside. Use when sizing a defensive stack, valuing a GK/DEF pick, scoring a candidate's BB2, or weighing the Clean Sheet Shield chip — called by wc-squad-architect, wc-matchday-tactician, wc-fitness-eval, and the strategists.

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wc-decision-board

Renders the FIFA World Cup Fantasy decision board — the advisory output that surfaces 2-4 genuinely distinct, weighted options for the expert manager and ends on "your call." Takes the evolution engine's verified offspring (with fitness decomposition, genotype lineage, and specialist dissent) and formats each as an option with its concrete picks, EV/ownership-leverage/variance/progression decomposition, football reasoning, what it's betting on, the dissent, and an ownership read — then a trade-off axis, a recommended-but-overridable default tied to the rank objective, and a "what I need from you." Enforces options-not-commands, shows the working, surfaces dissent, never auto-commits. Use to present any squad/matchday/transfer/chip decision.

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wc-decision-logger

Appends FIFA World Cup Fantasy decisions to tracker/decisions-log.md — logging not just what the manager chose but the full OPTION SET they chose from, which option the board recommended, whether the manager overrode it, and the manager's stated reasoning. Also archives the full generation (population → offspring → board → pick) to generations/, and updates the archetype scoreboard (which genotypes' blocks were chosen/won) and the manager's revealed preferences. Append-only; never overwrites. The override rows are the system's most valuable learning signal. Use after the manager picks an option off a board.

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wc-fitness-eval

Scores a FIFA World Cup Fantasy candidate squad/plan as risk-adjusted, rank-relative fitness under a stated rank objective (protect / gain / neutral). Sums fixture-scaled player xEV + captaincy uplift, adds clean-sheet correlation and progression-carry, applies an ownership-leverage term (cover chalk when protecting, fade it when gaining), and a variance term whose SIGN flips with the objective (penalty when protecting, reward when chasing) — the selection-pressure dial. Returns one fitness number plus the full decomposition. Use to score the population in the evolution engine, or to evaluate any single squad/plan. The objective makes the same candidate score differently for a leader vs a chaser; never returns raw expected points.

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wc-fixture-progression

Rates fixture difficulty (separately for an attacking and a defending fantasy asset, 1-5 each way, from opponent xGA/xG), computes team progression probabilities (group qualification odds from the mini-table; round-by-round knockout survival down the bracket) by reference-class forecasting updated Bayesianly on observed form and group state, detects weak-group/mismatch fixtures (powerhouse-vs-minnow -> captain candidates and clean-sheet locks), and builds a multi-round swing calendar of where each team's difficulty flips so transfers can be planned ahead. Emits the `fixture` signal. Use when called by wc-fixture-analyst, by the strategists in the populate stage, and by wc-fitness-eval for its progression_carry term — and never re-derive these once the signal exists.

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