Custom skill creator
Skill pngdeity/apm-user-repository/packages/custom-skill-creator/.apm/skills/custom-skill-creator
Meta-skill for creating and packaging new AI agent skills. Use when requested to create a skill, document a multi-step process, or configure agent behavior as a procedural skill module. Not for single atomic functions or global architecture constraints — those go in AGENTS.md.From its SKILL.md
npx -y skills add pngdeity/apm-user-repository --skill custom-skill-creatorAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
4.6 KB, 920 tokens by cl100k_base, as published. Nobody here has run it
Skill: Custom Skill Creator (custom-skill-creator)
This is the authoritative Meta-Skill for the pngdeity workspace. It extends the built-in skill creation process by enforcing the strict architectural boundaries of the "Abstraction Stack" and prioritizing validation and optimization based on agentskills.io standards.
Usage
Run this skill whenever requested to "create a skill," "document a process," or "configure agent behavior."
Phase 1: The Decision Heuristic (The Gate)
Before writing any files, you MUST evaluate the user's request against this logic. Do not create a SKILL.md if the request fails this gate.
- Global Constraint/Architecture? -> Write it in
AGENTS.md. (Refuse skill creation). - Single, Atomic Function? -> This is a Tool. Suggest a code implementation. (Refuse skill creation).
- Specialized, Multi-Step Workflow? -> This is a Skill. Proceed to Phase 2.
Phase 2: Skill Initialization & Drafting
- Create the skill directory manually:
mkdir -p skills/<skill-name>/references skills/<skill-name>/scripts- Create
SKILL.mdwith the YAML frontmatter template below. - If directory creation fails: Check write permissions and parent directory existence. Fall back to a single
SKILL.mdfile without subdirectories if needed.
- Read
references/agentskills-standards.mdfor frontmatter field rules andreferences/spec-authority.mdfor the canonical specification sources (agentskills.io, Microsoft Agent Framework, Anthropic Claude). - Draft the
SKILL.mdand any necessary scripts/references. Keep the main body under 500 lines (Progressive Disclosure). - Validate structure:
skills-ref validate ./skills/<skill-name>(ornpx skills-ref validatefrom the agentskills.io reference library).
Phase 3: Mandatory Validation
A skill is not complete until its behavior is validated.
- Define explicit test cases or dry-run instructions within the
SKILL.md(e.g., "Verification Step: Run script X and ensure output matches Y"). - If the skill relies on executable
scripts/, you MUST execute them locally to ensure they return LLM-friendly stdout (no massive tracebacks).
Phase 4: Optimization & Security (Post-Stability)
Once the SKILL.md is structurally sound and validated:
- Trigger Optimization: Review the YAML
description. It must function as an API doc for the agent router. Rewrite it to define exact trigger conditions. - Constraint Hardening: Ensure instructions use imperative mood and handle edge cases without hallucinating.
- Regenerate skill-index.json: Run
node skills/verification/generate-skill-index.cjsto rebuild the catalog index with updated tags and compatibility tokens from all SKILL.md files. - Security Review: Per the agentskills.io specification and Microsoft Agent Framework guidance (https://learn.microsoft.com/en-us/agent-framework/agents/skills):
- Review content: Read all skill files — instructions must not attempt to bypass safety guidelines, exfiltrate data, or modify agent configuration.
- Verify scripts: If
scripts/contains executables, confirm their behavior matches stated intent. Run them in an isolated environment first. - Check provenance: Only package skills from trusted sources. Prefer skills with version control history and active maintenance.
- Audit trail: Ensure the skill's
name,description, andcompatibilityfields are accurate and would not mislead a router. - If any security concern is found: Do not package. Document the finding and recommend remediation.
Packaging
Once Phase 4 is complete, make the skill discoverable:
- Validate:
skills-ref validate ./skills/<skill-name>(ornpx skills-ref validateif not installed globally).- If
skills-refis unavailable: Skip validation and note the gap. Proceed with structural verification (step 4) instead.
- If
- Register for cross-client discovery:
ln -sf <absolute-path-to-skill> ~/.agents/skills/<skill-name> - Run
node skills/verification/skill-compliance-check.cjsto confirm all checks pass.
What ships with it: 3 files
6.1 KB alongside SKILL.md
evals/
- evals.json1.2 KB
references/
- agentskills-standards.md2.5 KB
- spec-authority.md2.4 KB
Gives 0 of the 12 instructions most skill authoring skills give in 920 tokens
Counted across 408 of the 422 authors here whose files we hold, read 2026-09-06
- Keep SKILL.md under 500 linesin 118 of 408, across 104 files
- Write skill instructions in imperative formin 44 of 408, across 37 files
- Move detailed reference material into references filesin 41 of 408, across 34 files
- Run init_skill.py to initialize new skillsin 40 of 408, across 33 files
- Draft assertions while test runs are in progressin 32 of 408, across 25 files
- Keep description under 1024 charactersin 31 of 408, across 18 files
- Run package_skill.py once the skill is completein 29 of 408, across 23 files
- Spawn with-skill and baseline runs in the same turnin 28 of 408, across 21 files
- Test added scripts by actually running themin 27 of 408, across 21 files
- Follow the creation steps in orderin 24 of 408, across 17 files
- Generate the eval viewer before evaluating outputs yourselfin 24 of 408, across 17 files
- Write the description in third personin 24 of 408, across 18 files
Said here and by no other author read
- Evaluate the request against the decision gate before writing files
- Validate structure with skills-ref validate
- Define test cases or dry-runs inside the skill
- Execute bundled scripts locally to verify output
- Rewrite the description to define exact trigger conditions
- Regenerate the skill index after changes
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.