Writing Skills Skill | Agent Skills

Writing Skills

Overview

Writing skills IS structured documentation creation for process guidance.

Analyze requirements clearly, design skill structure thoughtfully, implement with precision, validate functionality, and iterate based on feedback.

Core principle: Clear requirements and structured design lead to effective skills that truly guide agent behavior.

Violating the letter of the rules is violating the spirit of the rules.

Routing

Pattern: Skill Steps Handoff: none Next: none

Task Initialization (MANDATORY)

Before ANY action, create task list using TaskCreate:

TaskCreate for EACH task below:
- Subject: "[writing-skills] Task N: <action>"
- ActiveForm: "<doing action>"

Tasks: 0. Fetch latest official skill spec

Analyze requirements
Design skill structure
Implement SKILL.md
Add references (if needed)
Validate structure
Review and improve
Test with real usage

Announce: "Created 8 tasks (0–7). Starting execution..."

Execution rules:

TaskUpdate status="in_progress" BEFORE starting each task
TaskUpdate status="completed" ONLY after verification passes
If task fails → stay in_progress, diagnose, retry
NEVER skip to next task until current is completed
At end, TaskList to confirm all completed

Skill Creation Process

| Phase | Focus | What You Do | |-------|-------|-------------| | Requirements | Understanding | Analyze what capability is needed and why | | Design | Structure | Plan skill organization, triggers, and content | | Implementation | Creation | Write skill following design and best practices | | Validation | Testing | Verify skill works correctly in real scenarios | | Improvement | Refinement | Iterate based on feedback and usage patterns |

Task 0: Fetch Latest Official Spec

Goal: Pull the current Anthropic skill spec before designing — never trust cached memory.

Action:

Skill tool: fetching-claude-docs
  component: skill
  question: "frontmatter fields (name, description), description trigger
             format, SKILL.md structure, references/ progressive disclosure,
             skill activation"

Verification: Received YAML with source: https://code.claude.com/docs/en/skills.md and non-empty spec_excerpt. Use as authoritative reference; if any rule in this SKILL conflicts with the fetched spec, the fetched spec wins.

Task 1: Analyze Requirements

Goal: Understand what skill to create and why. Present full analysis to user for confirmation.

Analyze and answer ALL questions below:

What capability does this skill teach?
What triggers should activate it? (specific phrases, symptoms)
Is this reusable across projects, or project-specific?
Does a similar skill already exist?
What are the key design decisions? List alternatives considered and chosen approach with rationale.

External search (optional): If claude-skills-mcp available, search for existing community skills to adapt.

MANDATORY: Present analysis to user. Display ALL answers above in full detail, then ask user to confirm before proceeding. Do NOT summarize into a single sentence. Do NOT skip to next task without explicit user approval.

Verification: User has reviewed the full analysis and confirmed the direction.

Task 2: Design Skill Structure

Goal: Plan the skill's organization, triggers, and content.

Before drafting, walk through prompt-design-principles.md:

5-skeleton framework — every skill needs Role, Scope, Workflow, Standards, Completion. Confirm each has concrete content planned.
Failure-mode reverse engineering — the Red Flags section should reflect specific failures you've observed or can predict, not generic warnings.
Conditional dispatch — list task variants the skill handles and per-variant behavior before writing absolute rules.
Creative-constraint balance — explicitly decide what can vary (form, solution options) vs. what must be fixed (process, verification, tool order).
Completion semantics — the final task must have a binary pass/fail check, not a narrative "done" signal.

Design considerations:

What specific capability does this skill provide?
When should the skill be triggered? (specific phrases, symptoms)
What are the key tasks and workflow steps?
What supporting materials are needed? (references, examples)

Structure planning:

Clear trigger conditions in description
Logical task sequence
Verification criteria for each task
Red flags and common mistakes

Verification: Have clear design plan with triggers, tasks, and structure defined.

Task 3: Implement SKILL.md

Goal: Create the skill following the design plan and best practices.

Skill Structure

skill-name/
├── SKILL.md           # Required (<300 lines)
├── scripts/           # Optional: executable tools
└── references/        # Optional: detailed docs

If the skill includes scripts: Use project's primary language if detectable (check package.json, go.mod, Cargo.toml, pyproject.toml, etc.); default to Python when unclear. Read cross-platform-scripts.md for mandatory cross-platform rules (paths, shell commands, line endings).

Naming Convention

Gerund form (verb + -ing): writing-skills, processing-pdfs

Lowercase, hyphens, numbers only
Max 64 characters
Avoid: helper, utils, anthropic, claude

SKILL.md Format

See references/spec.md for full frontmatter specification (fields, arguments, model selection, context:fork).

Context and Agent Selection

| Use Case | context | agent | Rationale | |----------|---------|-------|-----------| | Inline knowledge (conventions, patterns) | (none) | (none) | Runs in main conversation, Claude applies alongside current context | | Analysis or exploration task | fork | Explore | Isolated context, read-only tools, prevents context pollution | | Planning task | fork | Plan | Isolated context, research-focused | | Task with side effects (deploy, commit) | fork | (none) | Isolated from main conversation, uses general-purpose agent | | Default for most skills | (none) | (none) | Runs inline, cheapest, fastest |

When to use context: fork:

Skill generates large output that would pollute main context
Skill is a self-contained task (not reference material)
Skill needs different tools than the main conversation

When NOT to use context: fork:

Skill provides conventions or guidelines (needs main context to apply them)
Skill content is reference material for ongoing work
Skill needs access to conversation history

Key rules:

Name: gerund form, lowercase, hyphens only, max 64 chars
Description: starts with "Use when...", third person, does not summarize workflow
Body: < 300 lines, detailed content goes to references/
Parallel tool calls: when skill tasks involve independent reads, searches, or writes, explicitly state "run these tool calls in parallel" so the agent fans out instead of serializing

Body Structure

Required sections: Overview, Routing, Task Initialization, Tasks (with verification each), Red Flags, Common Rationalizations, Flowchart, References. See references/patterns.md for full template.

Verification

Can answer YES to all:

[ ] Description starts with "Use when..."
[ ] Description does NOT summarize workflow
[ ] Body < 300 lines
[ ] Has Task Initialization section
[ ] Has Red Flags section
[ ] Has verification criteria for each task

Task 4: Add References (if needed)

Goal: Move detailed content to references/ for progressive disclosure.

When to extract:

API documentation (100+ lines)
Detailed examples
Edge case handling
Background theory

Keep in SKILL.md:

Core workflow
Task definitions
Red Flags and Rationalizations
Quick reference tables

Verification: SKILL.md is < 300 lines. All detailed content has a reference link.

Task 5: Validate Structure

Goal: Verify skill structure is correct.

Use scripts/validate_skill.py to run automated validation:

python3 "${CLAUDE_SKILL_DIR}/scripts/validate_skill.py" <path/to/skill>

Manual checklist if script unavailable:

[ ] Frontmatter has name and description
[ ] Name is gerund form, lowercase, hyphens only
[ ] Description starts with "Use when..."
[ ] Body < 300 lines
[ ] All reference links work
[ ] If context: fork: model explicitly specified (inherit = anti-pattern in plugin skills)

Verification: Validation passes with no errors.

Task 6: REFACTOR - Quality Review

Goal: Have skill reviewed by skill-reviewer subagent.

Agent tool:
- subagent_type: "rcc:skill-reviewer"
- prompt: "Review skill at [path/to/skill]"

Interpret YAML output:

pass: true → Proceed to Task 7
pass: false → Fix all issues listed, re-run reviewer, repeat until pass: true

This is the improvement phase: Address issues and refine quality based on reviewer feedback.

Verification: skill-reviewer returns YAML with pass: true.

Task 7: Test with Real Usage

Goal: Verify skill works in practice.

Process:

Start new Claude Code session (fresh context)
Trigger skill naturally - use words from description, don't mention skill name
Verify skill activates
Verify agent follows instructions correctly
Run original pressure scenario WITH skill - agent should now comply

Verification:

Skill activates when triggered naturally
Agent follows skill instructions
Agent passes pressure scenario that failed in baseline

Red Flags - STOP

These thoughts mean you're rationalizing. STOP and reconsider:

"Skip requirements analysis, I know what's needed"
"Description can summarize the workflow"
"300 lines is too restrictive"
"Skip reviewer, the skill is obviously good"
"Testing is overkill for a simple skill"
"I'll add Red Flags later"
"Task list is too bureaucratic"

All of these mean: You're about to create a weak skill. Follow the process.

Common Rationalizations

| Excuse | Reality | |--------|---------| | "I know what agents need" | You know what YOU think they need. Baseline reveals actual failures. | | "Baseline testing takes too long" | 15 min baseline saves hours debugging weak skill. | | "Description should explain the skill" | Description = when to load. Body = what to do. Mixing causes skipping. | | "More content = better skill" | More content = more to skip. Concise + references = better. | | "Red Flags are negative" | Red Flags prevent rationalization. Essential for discipline skills. | | "TaskCreate is overhead" | TaskCreate prevents skipping steps. The overhead IS the value. |

Flowchart: Skill Creation

digraph skill_creation {
    rankdir=TB;

    start [label="Need new skill", shape=doublecircle];
    analyze [label="Task 1: Analyze\nrequirements", shape=box];
    baseline [label="Task 2: Design\nskill structure", shape=box];
    verify_red [label="Failures\ndocumented?", shape=diamond];
    write [label="Task 3: Write\nSKILL.md", shape=box];
    refs [label="Task 4: Add\nreferences", shape=box];
    validate [label="Task 5: Validate\nstructure", shape=box];
    review [label="Task 6: Quality\nreview", shape=box];
    review_pass [label="Review\npassed?", shape=diamond];
    test [label="Task 7: Test\nreal usage", shape=box];
    done [label="Skill complete", shape=doublecircle];

    start -> analyze;
    analyze -> baseline;
    baseline -> verify_red;
    verify_red -> write [label="yes"];
    verify_red -> baseline [label="no\nmore scenarios"];
    write -> refs;
    refs -> validate;
    validate -> review;
    review -> review_pass;
    review_pass -> test [label="pass"];
    review_pass -> write [label="fail\nfix issues"];
    test -> done;
}

References

references/spec.md - Frontmatter specification
references/patterns.md - Common skill patterns
references/examples.md - Before/after examples
references/persuasion-principles.md - Authority language research
references/testing-with-subagents.md - Baseline testing methodology
../../references/prompt-design-principles.md - 5-skeleton framework, failure-mode reverse engineering, conditional dispatch, creative-constraint balance, completion semantics

Agent Skills: Writing Skills

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Skill Files