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by shingo imotasimota/agent-skills85 stars
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Auditing SKILL.md normalization and compliance: scans the 21-item checklist, classifies violations, produces fix snippets. Use when auditing SKILL.md compliance or ecosystem health.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/gauge

This session only. Nothing lands on disk.

referenceofficial-standards.md

≈2.5k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Official Standards Reference

Source: "The Complete Guide to Building Skills for Claude" (Anthropic, 2025)

Official standards reference used by Gauge in the CLASSIFY / RECOMMEND phases.


1. Official 4-Phase Checklist

Phase 1: Before You Start

# Check Detail
1 Use case identification 2-3 concrete use cases defined
2 Tool inventory Built-in or MCP tools identified
3 Guide review Official guide and example skills reviewed
4 Folder structure plan Directory layout planned

Phase 2: During Development

# Check Detail
5 Folder naming kebab-case
6 SKILL.md existence Exact spelling SKILL.md (case-sensitive)
7 YAML delimiters --- present at start and end
8 name field kebab-case, no spaces, no capitals, matches folder
9 description field Includes WHAT + WHEN
10 No XML tags No < > anywhere in file
11 Clear instructions Actionable, not vague
12 Error handling Recovery steps included
13 Examples At least one usage example
14 References linked reference/ files properly referenced

Phase 3: Before Upload

# Check Detail
15 Trigger test — obvious Triggers on direct requests
16 Trigger test — paraphrased Triggers on rephrased requests
17 Negative trigger test Does NOT trigger on unrelated topics
18 Functional tests Core workflow completes successfully
19 Tool integration MCP/built-in tools work (if applicable)

Phase 4: After Upload

# Check Detail
20 Real conversation test Works in actual usage
21 Under/over-trigger monitor Trigger behavior observed
22 User feedback collection Feedback loop established
23 Iteration cycle Description and instructions updated based on feedback

2. Official Frontmatter Validation Spec

Required Fields

Field Format Constraint Validation Rule
name kebab-case No spaces, no capitals, no underscores Regex: ^[a-z0-9]+(-[a-z0-9]+)*$
description Free text ≤ 1024 chars, no XML tags (< >) Must include WHAT + WHEN (trigger phrases)

Security Restrictions

Rule Reason
No XML angle brackets in frontmatter Frontmatter appears in system prompt; prevents injection
No "claude" / "anthropic" in name Reserved prefixes
Safe YAML parsing only No code execution in YAML

Optional Fields

Field Format Constraint
license SPDX identifier e.g. MIT, Apache-2.0
allowed-tools Space-separated tool list e.g. "Bash(python:*) WebFetch"
compatibility Free text 1-500 characters
metadata YAML mapping Any key-value pairs (author, version, mcp-server, category, tags, etc.)

YAML Formatting Rules

# CORRECT — delimiters present
---
name: my-skill
description: Does things
---

# WRONG — missing delimiters
name: my-skill
description: Does things

# WRONG — unclosed quotes
---
name: my-skill
description: "Does things
---

File Naming Rules

Element Rule Example
SKILL.md Exact case-sensitive name SKILL.md ✅, skill.md ❌, SKILL.MD ❌
Skill folder kebab-case notion-project-setup ✅, Notion Project Setup ❌
No README.md Inside skill folder Documentation in SKILL.md or reference/ only

Note: The ecosystem's normalization-checklist.md uses a 16-item internal standard, while this official checklist is Anthropic's official quality standard. Meeting both is ideal.


3. Troubleshooting — 6 Categories

Category 1: Upload Failure

Error Cause Solution
"Could not find SKILL.md" Filename is not exact Verify with ls -la, rename to SKILL.md
"Invalid frontmatter" YAML format error Check --- delimiters, check for unclosed quotes
"Invalid skill name" Spaces or capitals in name Fix to kebab-case

Category 2: Skill Doesn't Trigger (Undertriggering)

Symptom: Skill never loads automatically

Diagnosis:

  • Description is too generic ("Helps with projects")
  • Missing trigger phrases
  • No mention of relevant file types

Solution: Improve the description — add specific keywords and technical terms

Debug method: Ask Claude "When would you use the [skill name] skill?"

Category 3: Skill Triggers Too Often (Overtriggering)

Symptom: Skill loads for unrelated queries

Solutions:

  1. Add negative triggers: "Do NOT use for simple data exploration"
  2. Clarify scope: "specifically for online payment workflows, not for general financial queries"
  3. Make the description more specific

Category 4: Instructions Not Followed (Execution Issues)

Symptom: Skill loads but Claude doesn't follow instructions

Diagnose the layer before rewording. "It was ignored" is a symptom, not a cause, and the reflex fix — adding emphasis — is the one intervention that reliably makes things worse. Work down this list in order and stop at the first layer that explains the behavior:

# Layer Check
1 Loading Did the file actually enter context? Wrong cwd, unmatched filename, empty file, truncation, or a post-compaction reload that never happened. Verify before anything else.
2 Scope It loaded, but does it apply to this task? Test the negative case too — a scoped rule leaking into unrelated work is the same defect inverted.
3 Ambiguity Can the line be read two ways? Rewrite as Condition + Directive + Verification + Boundary: not "run relevant tests" but "on src/api/** changes run make test-api; add make test-contract for public schema changes."
4 Conflict List every source touching this action — root, package, local, managed, task prompt, hook/CI — before editing any one of them.
5 Context overload The rule is clear but buried. Remove duplicates, scope the loading, move procedures to reference/.
6 Capability Does the session have the tool the rule assumes? If not, the rule needs a stated fallback, not stronger wording.
7 Enforceability A constraint that must hold even under pressure belongs in a hook or permission rule — see _common/MECHANISM_SELECTION.md.
8 Variability Adherence is never 100%. Do not conclude from one run; reproduce before rewriting.

Do not add emphasis as a first move. More IMPORTANT / CRITICAL markers inflate priority across the whole file: when everything is critical, nothing is, and the markers stop carrying signal. Anthropic measured a 3% intelligence drop from this class of pressure wording, and it does not surface in task-level evals — _common/OPUS_5_AUTHORING.md. Reserve emphasis for the few constraints that genuinely outrank the rest, after layers 1-4 are ruled out.

Then apply the ordinary fixes: concise bullets with detail moved to reference/, key rules placed early, and a bundled script wherever the check can be made deterministic.

Category 5: MCP Connection Issues

Symptom: Skill loads but MCP calls fail

Checklist:

  1. MCP server connected (Settings > Extensions)
  2. Authentication valid (API keys, OAuth tokens, permissions/scopes)
  3. MCP independent test: "Use [Service] MCP to fetch my projects" — failure = MCP issue, not skill
  4. Tool names correct (case-sensitive)

Category 6: Large Context Issues

Symptom: Slow responses or degraded quality

Causes: Skill content too large, too many skills enabled, no progressive disclosure

Solutions:

  1. Optimize SKILL.md to under 5,000 words
  2. Move details to reference/
  3. If 20-50+ skills are enabled simultaneously, enable selectively
  4. Group related features with Skill packs

4. Quality Signals

Quantitative Metrics

Metric Target Measurement Method
Trigger rate 90%+ on relevant queries Run 10-20 test queries, track automatic loading vs explicit invocation
Workflow efficiency Complete in X tool calls Compare same task with/without skill, count tool calls and tokens
API reliability 0 failed API calls per workflow Monitor MCP server logs, track retry rates and error codes

Qualitative Metrics

Metric Assessment Method
No next-step prompting needed During testing, note how often redirect/clarification is needed. Ask beta users.
Workflow completes without correction Run same request 3-5 times, compare structural consistency and quality
Consistent cross-session results Can a new user accomplish the task on first try with minimal guidance?

5. Distribution Requirements

Distribution Surfaces

Surface Method
Claude.ai Settings > Capabilities > Skills > Upload (zip)
Claude Code Place in skills directory
API /v1/skills endpoint, container.skills parameter
Organization Admin workspace-wide deployment (centralized management, automatic updates)

Positioning Best Practices

Do Don't
Focus on outcomes Focus on technical implementation
Highlight MCP + Skills story Describe folder structure
Provide installation guide Assume users know the process

GitHub Distribution

  1. Public repo with clear README (repo-level, NOT inside skill folder)
  2. Link from MCP documentation
  3. Include quick-start guide with screenshots

Source: SKILL.md on GitHub

1 warning13d4 checks · Risk MEDIUM
  • Gen Agent Trust Hub13d

    The Gauge skill audits other AI agent skills for compliance and contains a self-evolution mechanism to update its own instructions via web research. It is vulnerable to indirect prompt injection from audited files and involves dynamic instruction modification.

  • Socket13d

    No alerts

  • Snyk13d

    Risk: LOW · No issues

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at 35ffd55. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 3 days ago.

Activeupdated 2 weeks ago

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