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AC issue-fields-migration

Bulk-migrate metadata to GitHub issue fields from two sources: repo labels (e.g. priority labels to a Priority field) and Project V2 fields. Use when users say "migrate my labels to issue fields", "migrate project fields to issue fields", "convert labels to issue fields", "copy project field values to issue fields", or ask about adopting issue fields. Issue fields are org-level typed metadata (single select, text, number, date) that replace label-based workarounds with structured, searchable, cross-repo fields.

github/awesome-copilot Agent Skills author: github MIT 4 files body ≈ 5 910 tokens Open the sourcegithub.com↗ analyzed 28 h ago

Bulk-migrate metadata to GitHub issue fields from two sources: repo labels (e.g. priority labels to a Priority field) and Project V2 fields. Use when users…

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers

ProcedureGitHubAI and agentstype and topics are labelled automatically from the skill text
Runs in: GitHub Copilot / VS Code Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
97
Quality 40%
83
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Tools and files w 18
60
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: RA-Skills

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 3

✓ No critical or high findings

Medium and low: 3
  • low Secrets in code secret-high-entropy-token references/projects-api.md:98
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    ... on Proj…lue { name field { ... on Proj…eld { name } } }
    placeholder
  • low Secrets in code secret-high-entropy-token references/projects-api.md:99
    High-entropy token-like string (may be an id, hash or a credential) (placeholder value)
    ... on Proj…lue { number field { ... on Proj…eld { name } } }
    placeholder
  • low Secrets in code secret-high-entropy-token references/projects-api.md:116
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **Field value access**: each field value node type is different (`Proj…lue`, `Proj…lue`, etc.). Handle each type.
    quoted

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5910 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 343): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 61/100

  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Failures and branches. 7 branches
  • 70Execution cost. Instruction body is 5910 tokens
  • 100Steps. 106 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 516: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 106 items
  • +4Has examples (21 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.