hsa-receipt-vault
Maintains a ledger of HSA-qualified medical expenses paid out of pocket (not reimbursed from the HSA), each with date, amount, provider, description, and a path to the scanned receipt. Tracks the running unreimbursed total — the amount of HSA balance the household can pull tax-free at any future date — and validates each candidate against IRS-qualified-expense categories. Use when a new medical receipt arrives, when totaling future tax-free HSA reimbursements, when planning a deferred reimbursement, or when user mentions HSA receipt vault, qualified medical expenses, or HSA shoebox strategy.
hypotheticals-counterfactuals
Applies "what if" thinking to explore alternative scenarios, test assumptions, understand causal relationships, and prepare for uncertainty. Guides through counterfactual reasoning, scenario exploration, pre-mortem analysis, and stress testing decisions against alternative futures. Use when exploring alternative scenarios, testing assumptions through "what if" questions, understanding causal relationships, conducting pre-mortem analysis, stress testing decisions, or when user mentions counterfactuals, hypothetical scenarios, thought experiments, alternative futures, what-if analysis, or needs to challenge assumptions.
identify-kill-list
Names what the substacker writer should stop doing — habits with no evidence of use, goals that became theatre, sections with 2 consecutive dormant quarters, and agents in the team whose output the writer ignores. Produces a bulleted list, each item with one sentence of why. Max 4 items. Ordered by ease (easiest first). Used once per Growth Strategist review. Trigger keywords — kill list, stop doing, what to cut, dead habits, dormant, ignored output.
information-architecture
Organizes, structures, and labels content so users can find and manage information effectively. Guides through content audits, card sorting, taxonomy design, navigation structure, and tree testing validation. Use when organizing content for digital products, designing navigation systems, restructuring information hierarchies, improving findability, creating taxonomies or metadata schemas, or when users mention information architecture, IA, sitemap, navigation design, content structure, card sorting, tree testing, taxonomy, or findability.
ingest-inbox-item
Ingests a single file from the substacker inbox/ into corpus/seeds/ as a normalized markdown seed with full frontmatter. Orchestrates format normalization, topic tagging, intuition-density scoring, dedupe, changelog, ledger update, and inbox-file move to .processed/. Use when the user drops raw material into inbox/ and runs /ingest, at session start, or whenever a single inbox file needs to become an indexed seed. Trigger keywords — ingest, inbox, new note, new transcript, new highlight, index this, add to corpus.
ingest-substack-csv
Loads and validates a weekly Substack CSV stats export for the substacker Growth Analyst. Reconciles header against expected-columns schema, parses post rows + subscriber aggregates, moves file into corpus/stats/ on success, emits schema-warning stub on header drift. Never reads subscriber emails row-by-row — aggregates only. FALLBACK path when fetch-substack-stats (Chrome automation) is unavailable. Use when a CSV appears in inbox/substack-stats/, when Chrome is not logged in, or when the writer prefers manual export. Trigger keywords — CSV, Substack export, stats export, schema validation, subscriber data, manual export, CSV fallback.
inspectional-reading
Domain-neutral methodology for the first level of Adler-style reading - systematic skimming to determine what kind of document this is, what it's about as a whole, and whether deeper engagement is worth the time investment. Read title, metadata, table of contents or section headings, abstract or introduction, conclusion, and end-material at a glance. Classify document type (methodology, framework, tool, theoretical, reference, or hybrid). Decide whether to escalate to deeper reading. Reusable across any artifact-from-document workflow - paper extraction, skill creation from a methodology document, literature triage, reading-list pruning. Use when an agent needs to convert "I have a document, what is it" into structured downstream-actionable input. Trigger keywords - inspectional reading, systematic skimming, document classification, Adler reading, skim before reading, skill-worthiness check, paper triage, reading triage.
kill-criteria-exit-ramps
Establishes pre-defined, objective conditions for stopping projects and specific decision points for continue/pivot/kill evaluations. Guides through defining kill criteria, setting go/no-go gates, avoiding sunk cost fallacy, and executing disciplined stopping decisions. Use when defining stopping rules for projects, avoiding sunk cost fallacy, setting objective exit criteria, deciding whether to continue/pivot/kill initiatives, or when users mention kill criteria, exit ramps, stopping rules, go/no-go decisions, project termination, or sunk costs.
knowledge-graph-construction
Designs and builds knowledge graphs from unstructured or semi-structured data sources. Guides through data model selection (LPG, RDF, hypergraph, temporal), schema design, entity/relation extraction pipelines, and layered architecture construction. Use when designing knowledge graphs, choosing between LPG vs RDF, planning entity extraction, designing graph schemas, aligning ontologies, building a KG for RAG, or when user mentions knowledge graph construction.
ladder-of-abstraction
Moves prose deliberately between the concrete and the abstract and stops it stranding in the middle rung where bureaucratic prose lives. Tags every paragraph R1 (named particulars) to R4 (meaning), enforces run rules, detects the middle-rung trap, repairs it by climbing down to a real particular rather than simplifying vocabulary, gates the top rung with a counter-sentence test, and closes with an A-frame descent. Use when a draft reads as dense, vague, or jargon-heavy, when a readability score fails, when a conclusion feels grandiose or unearned, when technical material will not land for a general reader, or when user mentions ladder of abstraction, too abstract, too vague, concrete example, middle rung, dead zone, jargon, altitude, zoom in, zoom out, and thus capitalism.
layered-reasoning
Structures thinking across multiple abstraction levels (30,000 ft strategic, 3,000 ft tactical, 300 ft operational) while maintaining consistency between layers. Guides through top-down decomposition, bottom-up aggregation, cross-layer translation, and constraint propagation. Use when reasoning across multiple abstraction levels, designing systems with hierarchical layers, explaining concepts at different depths, maintaining consistency between principles and implementation, or when users mention 30,000-foot view, layered thinking, abstraction levels, top-down design, or strategy-to-execution alignment.
learning-in-public-voice
House style for learning-in-public essays — a curious practitioner thinking out loud while learning a hard technical subject (here, ML-driven crop genetics / genomic selection). First-person, concrete-first, honest about the edge of understanding, mechanism over vocabulary. Provides the register, the hook patterns, the anti-slop hard rules, and the rule for reading a per-writer voice-profile.md so the voice stays the writer's own. Use when drafting a vault-style post from evergreen notes, or as the lens an advisory editor critiques against. This skill never imposes voice; it describes defaults and defers to the writer's profile.
linkedin-post-rewrite
Rewrites a published substacker essay as a LinkedIn post with a hook fitting the 210-char fold, practitioner framing (less confessional than Substack), short 2-3 line paragraphs, and 0-2 niche hashtags. 900-2500 characters. Emits linkedin-post.md. Use as the LinkedIn-native arm of the Distribution Translator. Trigger keywords — LinkedIn post, LinkedIn rewrite, practitioner, professional network, niche hashtags.
map-analogy-to-concept
Produces an explicit component-by-component mapping from the analogy's source domain to the target technical concept. Rejects vague analogies by forcing each source element to map to a specific target element, and flags unmapped elements as voice-breaking ("it's like a brain" is rejected because "brain" is unmapped). Use after generate-analogy-set, for each of the 5 framings. Trigger keywords — map, component mapping, source target, explicit mapping, what does the X correspond to.
mapping-visualization-scaffolds
Creates visual maps that make implicit relationships, dependencies, and structures explicit through diagrams, concept maps, and architectural blueprints. Guides through identifying nodes and relationships, choosing visualization approaches, and validating completeness. Use when complex systems need visual documentation, mapping component relationships and dependencies, creating hierarchies or taxonomies, documenting process flows or decision trees, understanding system architectures, visualizing data lineage or knowledge structures, or when user mentions concept maps, system diagrams, dependency mapping, relationship visualization, or architecture blueprints.
markdown-to-pdf
Renders a markdown report to a PDF using pandoc with xelatex (11pt serif body, 1-inch margins, numbered footnotes, formal heading hierarchy). Requires a one-time install of pandoc and a LaTeX engine on the user's machine — basictex on macOS or texlive-xetex on Linux. Does not attempt automatic install. Fails loudly with the exact install commands if pandoc or xelatex is missing on the user's PATH. Use when producing a finished strategist or analyst report PDF from a polished markdown source.
market-mechanics-betting
Translates beliefs (probabilities) into optimal actions (bet/pass/hedge) using quantitative frameworks including edge calculation, Kelly Criterion bet sizing, forecast extremizing, and Brier score optimization. Use when converting probabilities into decisions, calculating edge against market odds, sizing bets optimally, extremizing aggregated forecasts, improving Brier scores, or when user mentions betting strategy, Kelly Criterion, edge calculation, Brier score, extremizing, or translating belief into action.
mastery-assessment
A closed-book-first probing protocol that assesses how well the learner actually holds a module's claims — asking before telling, probing the gap, detecting misconceptions, then confirming. Tags each probe with a Bloom level, places the learner in a Dreyfus mastery band (unfamiliar/aware/functional/proficient/fluent), scores the session, and schedules the next spaced-repetition surfacing on expanding intervals (1d, 3d, 7d, 16d, 35d) — pulling the next date earlier on a miss. Writes an assessment-session note to assessments/log/ and proposes a review-due update on each evergreen note touched. Use when checking mastery of a module, running a spaced-repetition review, or gating phase progression. Trigger keywords — assess mastery, review-due, spaced repetition, Bloom check, mastery band, am I ready to move on.
matchup-win-probability-sim
Computes P(we win at least K of N categories) for a head-to-head categorical matchup via Monte-Carlo simulation or Poisson-binomial approximation. Domain-neutral — works for any fantasy sport with H2H Categories scoring (MLB, NBA, NHL) or any zero-sum per-category competition. Use when you need matchup_win_probability, per_cat_win_probability, expected_cats_won, or variance_estimate; or when user mentions "matchup win probability", "head to head simulation", "Monte Carlo matchup", "Poisson binomial matchup", "P win 6 of 10", "category matchup simulation", or "weekly win probability".
mcphee-structure-derivation
Derives a document's structure out of its own corpus instead of picking one off a menu, using John McPhee's coding-and-sorting procedure - cold read, short topic codes one per card, a strict chronology sort run against a strict theme sort, a logged list of every disagreement resolved toward chronology, candidate juxtapositions gated by a state-and-footnote test, a named shape, and an invisibility test. Use when you hold researched material and have no structure yet, when a draft has turned into concept-named sections full of time-scrambled evidence, when deciding whether a flashback is earned, or when user mentions McPhee, coding pass, index cards, deriving structure, chronology versus theme, structure from material, or "what shape is this piece".
memory-retrieval-learning
Creates evidence-based learning plans that maximize long-term retention through spaced repetition, retrieval practice, interleaving, and elaboration. Guides through goal definition, material breakdown, review scheduling, and progress tracking. Use when long-term knowledge retention is needed, studying for exams or certifications, learning new job skills or technology, mastering substantial material, combating forgetting, or when user mentions studying, memorizing, learning plans, spaced repetition, flashcards, active recall, or durable learning.
meta-prompt-engineering
Transforms vague or unreliable prompts into structured, constraint-aware prompts with explicit roles, task decomposition, output formats, and quality checks. Use when prompts produce inconsistent outputs, need explicit structure and constraints, require safety guardrails, involve multi-step reasoning that needs decomposition, need domain expertise encoding, or when user mentions improving prompts, prompt templates, structured prompts, prompt optimization, reliable AI outputs, or prompt patterns.
metrics-tree
Decomposes high-level North Star metrics into actionable sub-metrics and leading indicators, maps causal relationships between metric levels, and identifies high-impact experiments to move key metrics. Use when setting product North Star metrics, decomposing business metrics into drivers, mapping strategy to measurable outcomes, identifying which metrics to move through experimentation, understanding leading vs lagging indicators, prioritizing metric improvement opportunities, or when user mentions metric tree, metric decomposition, North Star metric, KPI breakdown, metric drivers, or how metrics connect.
ml-primitive-decoder
Decomposes any ML construct (attention, layer norm, softmax, convolution, dropout, contrastive loss, diffusion step, gradient descent update, cross-entropy) into the small set of linear-algebra primitives it's built from, then explains why those primitives produce the observed behavior. Includes an ablation thought experiment that asks "what would break if you removed this piece?". Use when the user asks "why does X work?", "explain attention/conv/norm intuitively", "what's actually happening in this layer", or when reading an architecture paper and a particular block doesn't make sense yet.
mlb-beginner-translator
Converts baseball and fantasy-baseball jargon into plain English for a user with zero baseball knowledge. Wraps every user-facing sentence produced by the MLB agent team (morning briefs, trade recommendations, waiver calls, chat summaries). Detects jargon terms, attaches an inline parenthetical plain-English gloss on first mention in a document, enforces the action-verb ladder (START / SIT / ADD / DROP / BID $X / ACCEPT / COUNTER / REJECT), and rejects assumed-knowledge phrases like "hot streak" or "positive matchup." Use when asked to translate for beginner, explain in plain English, translate this, write without jargon, make it beginner-friendly, or produce any user-facing MLB output for K L D'Souza's Fantasy Baseball 2K25 team.
mlb-category-state-analyzer
Computes the weekly category state for a Yahoo H2H Categories matchup across all 10 scoring categories (R, HR, RBI, SB, OBP, K, ERA, WHIP, QS, SV). Pulls current totals from Yahoo, builds rest-of-week per-cat projections from roster + schedule, then DELEGATES matchup/per-cat win-probability math to `matchup-win-probability-sim`. Consumes the sim's `per_cat_win_probability` and `matchup_win_probability` to derive cat_position, cat_pressure, cat_reachability, and cat_punt_score, and emits a "push 6, punt N" plan that drives waiver, streaming, and lineup decisions. Use when user asks about "category state", "where am I winning", "should I punt", "matchup score", "cat pressure", weekly category planning, or which cats to push vs. concede.
mlb-closer-tracker
Tracks the closer role and bullpen pecking order across all 30 MLB teams — who owns the ninth-inning job today, who is next in line if the current closer falters (the handcuff), and who carries DFA or demotion risk. Emits a per-reliever `save_role_certainty` signal (0-100) and flags speculation-worthy handcuffs for waiver bids. Use when the user mentions "closer", "save role", "handcuff", "ninth inning", "bullpen depth", lost save, blown save, committee, or when the waiver analyst needs to decide whether to spend FAAB on a backup reliever. This league uses SV as one of its five pitcher categories, but SV is also the most volatile and most punt-worthy cat, so tracking should always be paired with a punt-the-cat fallback recommendation.
mlb-decision-logger
Appends structured decision entries to the yahoo-mlb decision log (tracker/decisions-log.md) on behalf of any agent in the MLB team. Validates entries against the authoritative schema, serializes concurrent writes from parallel agents, and runs the Monday calibration pass to fill in outcomes and update the variant scoreboard. Use when any MLB agent needs to record a decision, when the coach requests "log decision", "append to decision log", "record variant outcome", or runs the "calibration pass".
mlb-faab-sizer
Computes FAAB (Free Agent Acquisition Budget) recommended and maximum bids for Yahoo fantasy baseball waiver targets. Implements the baseball-specific layering of the faab-bid-framework (positional_need_fit, role_certainty, urgency, season_pace, league-inflation calibration) and DELEGATES the game-theoretic primitives -- first-price shading and winner's-curse haircut -- to the sibling skills `auction-first-price-shading` and `auction-winners-curse-haircut`. Produces a recommended bid, a hard ceiling, a rationale with the full delegation chain, and guardrail flags. Use when the user asks "how much should I bid on X", mentions FAAB bid, waiver bid amount, blind bid, Yahoo waiver claim sizing, or when mlb-waiver-analyst needs a bid amount for an identified target.
mlb-league-state-reader
Parses Yahoo Fantasy Baseball league state (roster, standings, current matchup, FAAB remaining, free agents) from authenticated Yahoo team pages via Claude-in-Chrome browser automation, then grounds it against league-config.md and team-profile.md to emit a normalized league-state bundle every other agent can consume without re-scraping. Use when the coach or any downstream agent needs to read Yahoo roster, refresh team profile, pull league state, get current matchup, check FAAB remaining, list free agents, or when user mentions "what's on my roster", "who am I playing this week", "how much FAAB do I have left", or "refresh my team".
mlb-matchup-analyzer
Analyzes a single MLB game from a fantasy perspective given home team, away team, and date. Emits structured matchup signals -- opp_sp_quality, park_hitter_factor, park_pitcher_factor, weather_risk, bullpen_state -- and a short narrative of platoon implications (handedness matchup for hitters). Use when preparing daily start/sit calls, evaluating a streaming pitcher's environment, sizing weather risk, or when user mentions matchup analysis, park factor, opposing pitcher, weather risk, or platoon.
mlb-opponent-profiler
Weekly refresh of per-opponent archetype + behavioral profiles for the 11 opposing teams in the user's Yahoo Fantasy Baseball league (ID 23756). Thin baseball-specific wrapper around the domain-neutral `opponent-archetype-classifier` -- provides the 10-archetype MLB taxonomy (balanced, stars_and_scrubs, punt_sv, punt_sb, punt_wins_qs, hitter_heavy, pitcher_heavy, inactive, frustrated_active, unknown), extracts MLB features from Yahoo pages (draft distribution, FAAB spend, waiver pattern, roster composition, lineup consistency, trade activity, recent record, activity recency), invokes the classifier, and writes/updates `context/opponents/<team-slug>.md` files per `opponent-profile-schema.md`. Read-modify-write preserves manual notes. Emits a weekly summary signal at `signals/wkNN-opponent-profiles.md`. Use when user says "opponent profiling", "classify opposing manager", "update opponent profiles", "refresh opponents", "weekly opponent scout", or "MLB fantasy opponent archetype".
mlb-player-analyzer
Deep-dive analysis of a single MLB player (hitter or pitcher) for the Yahoo Fantasy Baseball 2K25 league. Web-searches FanGraphs (ATC projections), Baseball Savant (xwOBA/xBA/xERA), MLB.com (lineups, probables), RotoWire (weather, injuries), and RotoBaller (closer depth) to produce the full set of structured player signals defined in the signal framework. Emits form_score, matchup_score, opportunity_score, daily_quality, regression_index, obp_contribution, sb_opportunity, role_certainty for hitters and qs_probability, k_ceiling, era_whip_risk, streamability_score, two_start_bonus, save_role_certainty for pitchers. Use when you need to analyze player, compute daily_quality, compute regression index, produce player signals, run a hitter analysis, run a pitcher analysis, or prep start/sit inputs for the lineup optimizer.
mlb-playoff-scheduler
Counts MLB games per team during the Yahoo fantasy playoff window (weeks 21, 22, 23 -- Aug 17 through Sep 6, 2026) and grades the quality of each team's opponents. Emits three signals per rostered player -- playoff_games (int, max ~21), playoff_matchup_quality (0-100), holding_value (0-100) -- that drive trade-deadline and playoff-lineup decisions. Use when the user mentions playoff weeks, weeks 21-23, playoff schedule, game count, holding value, or asks whether to keep/trade a player for the playoff run. Pre-July 1 this skill returns "insufficient signal -- too early"; from July 1 onward it fires weekly.
mlb-regression-flagger
Identifies fantasy baseball players whose surface stats (wOBA, ERA, batting average) are diverging from their underlying Statcast quality (xwOBA, FIP, xBA) — emits a `regression_index` from -100 (very lucky, sell high) to +100 (very unlucky, buy low). Primary signal for buy-low/sell-high decisions on trades and waivers. Use when user mentions "buy low", "sell high", "regression candidate", "lucky", "unlucky", "xwOBA gap", "ERA-FIP gap", "BABIP", "due for regression", or is deciding whether to trade for / trade away a player based on over- or under-performance.
mlb-signal-emitter
Validates and persists signal files to the yahoo-mlb signals directory. Every MLB skill calls this skill before writing a signal. Enforces the signal-framework.md schema -- required YAML frontmatter fields (type, date, emitted_by, confidence, source_urls), range-checks numeric signals (0-100 unipolar, -100 to +100 bipolar), verifies variant_synthesis metadata, and enforces file naming. On validation failure, does not persist and routes a failure entry to mlb-decision-logger. Use when an agent or skill needs to emit a signal, validate a signal file, write to signals/YYYY-MM-DD-<type>.md, or check signal frontmatter. Triggers — "emit signal", "validate signal", "write signal file", "signal frontmatter".
mlb-trade-evaluator
Computes the full impact of a proposed MLB fantasy trade across all 10 H2H categories (R/HR/RBI/SB/OBP, K/ERA/WHIP/QS/SV), rest-of-season dollar value, positional flexibility, slot-value optionality, adverse-selection prior, and weeks 21-23 playoff impact. Produces a signed verdict (accept / counter / reject) with rationale and a specific counter if applicable. Use when user mentions "trade evaluation", "trade value", "should I accept", "trade delta", "counter offer", or pastes in a trade proposal from Yahoo. Defaults to COUNTER in the middle band — pure REJECT is reserved for clearly predatory offers.
mlb-two-start-scout
For a given fantasy week (Monday-Sunday), identifies every starting pitcher scheduled to start twice, validates both probable starts, grades each matchup against the league's Quality Starts (QS) scoring rules, and ranks the list by streamability_score. Flags bullpen-game and opener risks that nearly never produce QS. Use when user mentions "two-start pitchers", "weekly streaming", "Monday-Sunday pitcher plan", "double start", "2-start SP", or preparing the weekly streaming plan on Sunday nights.
model-equivariance-auditor
Verifies that implemented neural network models correctly respect their intended symmetries through systematic equivariance testing, layer-wise isolation, and gradient analysis. Use when testing model equivariance, debugging symmetry bugs, verifying implementation correctness, checking if a model is actually equivariant, or diagnosing why an equivariant model isn't working.
monte-carlo-valuation
Turns a point-estimate valuation into a distribution — samples the drivers you are least sure about from normal, lognormal, triangular, uniform or discrete-scenario distributions, re-runs the DCF engine on every draw, and reports percentiles, mean, standard deviation, the probability the value exceeds the market price, and the share of draws the engine refused as infeasible. Correlates drivers through a shared common factor. Use when running a Monte Carlo simulation or a probabilistic valuation, putting a range or confidence band around a value per share, asking how likely it is that a stock is under- or overvalued, valuing a commodity or cyclical company where one macro variable such as the oil price dominates, or turning a scenario grid into a probability-weighted expected value.
morphological-analysis-triz
Explores solution spaces systematically through morphological analysis (parameter-option matrices) and resolves technical contradictions using TRIZ inventive principles to generate novel, non-obvious solutions. Use when exploring all feasible design alternatives before prototyping, resolving technical contradictions (speed vs precision, strength vs weight, cost vs quality), generating novel product configurations, finding inventive solutions to engineering problems, identifying patent opportunities, or when user mentions morphological analysis, Zwicky box, TRIZ, inventive principles, systematic innovation, or design space exploration.
narrative-arc-mapping
Maps researched evidence onto Truby's twenty-two structural steps without fabricating the steps the evidence cannot fill. Runs the designing-principle discrimination test, step-fit triage (PRESENT / ABSENT / NOT APPLICABLE), per-slot warrant cards, the empty-slot decision table, the moral-argument spine, and the revelation-intensity audit, then stops at a tagged scene weave. Use when architecting a long-form nonfiction piece from a research corpus, structuring a post-mortem, market history, biography, or science writeup, or when user mentions Truby, 22 steps, designing principle, moral argument, revelation sequence, scene weave, or step-fit triage.
narrative-evidence-ledger
Builds the evidence ledger that narrative work is allowed to be built on, before any structure is chosen. Locks the frame (unit, denominator, window, population boundary), atomizes material into findings with evidence classes A-F and re-findable pointers, triages every causal claim L1 MECHANISM to L5 CONJECTURE with permitted and banned verb sets, runs one-way promotion from finding to claim to beat, and keeps a DEAD column of everything a veto killed. Use before outlining or drafting any evidence-based narrative, when auditing whether a draft's claims are actually sourced, when a piece needs a provenance layer for handoff, or when user mentions evidence ledger, claim ledger, provenance, sourcing, causal grading, denominator lock, cherry-picking, or circular citation.
narrative-fallacy-guard
Stops a true set of facts from being assembled into a false story. Runs the retrospective slot audit, the outcome-blind rewrite (flip test, separation test), the inevitability audit with its overshoot check, the survivorship graveyard pass, the counterfactual admissibility gate, and the expensive proportion and omission audits. Every check labels and discloses; none deletes. Use when drafting or reviewing history, post-mortems, biography, market or protocol narratives, research writeups, or any account written after the outcome was known, or when user mentions hindsight bias, narrative fallacy, survivorship bias, inevitability, halo effect, outcome bias, just-so story, teleology, or Whig history.
narrative-fidelity-audit
Runs the hard gate on invention in fact-based narrative — a bright-line refusal sweep, an interior-state provenance ladder ([A] said-so / [B] contemporaneous document / [C] behavioural inference / [D] unsourced, where any [D] blocks publication), an LLM-specific fabrication red-flag scan, a three-altitude "How do you know?" prosecution at sentence, paragraph and passage level, a subtraction-log set review, and a note on sources generated from the deviation log. Use before shipping any narrative built on real evidence — market history, incident post-mortem, biography, ML writeup, supply-chain reconstruction, science writing — or when the user mentions fact-check, fidelity audit, fabrication check, invented detail, sourcing pass, did I make this up, composite scene, note on sources, or is this defensible.
narrative-form-triage
Decides which narrative form a body of researched material can actually support, before any structure is imposed. Runs a six-question form-triage gate producing STORY NARRATIVE, EXPLANATORY NARRATIVE, MULTI-NODE GATHERING, or DO NOT NARRATE; runs the ABT (And/But/Therefore) spine diagnostic; selects a spine from a thirteen-structure table covering Truby arc, layer cake, pyramid/SCQA, OCAR, PR/FAQ, sparkline, Raskin five-slot, martini glass, drill-down, inverted pyramid and braided/mosaic; and writes an immutable spine contract with a boredom budget. Use before outlining or drafting any long-form nonfiction, report, post-mortem, market history, research writeup or case study, or when user mentions find the narrative, what's the story here, narrative arc, story structure, how should I structure this, does this have a story, or storytelling with data.
narrative-handoff-contract
Defines and validates the machine-readable contract that passes a narrative architecture between a structural agent and a drafting agent — architecture.json with evidence-backed slots, capped scene tags, gap dispositions, a DEAD column, and an escalation object for sending defects back upward. Ships a validator script so the rules are enforced rather than requested. Use when two agents or two sessions must hand narrative work to each other, when an architecture needs checking before drafting begins, when a draft must report a defect it cannot fix at its own layer, or when the user mentions handoff, contract, schema, validator, architecture.json, escalation, or "the outline and the draft have drifted apart".
narrative-opposition-web
Builds a four-corner opposition web for narrative nonfiction and stops the writer from casting whoever lost as the villain. Runs Truby's four-corner worksheet (shared central moral problem, per-corner value clusters, distinct routes of attack, corner-to-corner conflict), the best-possible-opponent audit (same goal, necessity, relentlessness, value conflict, the double, power parity, justification in the opponent's own voice), the Opponent Warrant evidence test that demotes undocumented antagonists to rivals or constraints, and a drive-section collapse check that catches a web that was decorative. Use when planning a piece with competing parties, when an antagonist feels flat or cartoonish, when the protagonist is a system rather than a person, or when user mentions opposition web, four-corner opposition, antagonist, opponent, villain, steelman the other side, character web, who is the bad guy here.
narrative-to-numbers
Builds the business story behind a valuation and connects it to the drivers that carry value — market size, growth, margin, reinvestment efficiency and risk. Tests a narrative as possible, plausible and probable, and keeps the feedback loop open. Use when starting a valuation, writing the story behind a company, setting growth or margin assumptions, sanity-checking a story against its numbers, choosing a target margin or sales-to-capital ratio, or when a valuation needs a defensible reason for its inputs.
negative-contrastive-framing
Defines concepts, quality criteria, and boundaries by showing what they are NOT -- using anti-goals, near-miss examples, and failure patterns to create crisp decision criteria where positive definitions alone are ambiguous. Use when clarifying fuzzy boundaries, defining quality criteria, teaching by counterexample, preventing common mistakes, setting design guardrails, disambiguating similar concepts, refining requirements through anti-patterns, or when user mentions near-miss examples, anti-goals, what not to do, negative examples, counterexamples, or boundary clarification.
Page 3 of 6 · 271 results