validate-skills
Skill976 starsChanged 6 months agoMITView on GitHub
Validate that commands documented in skill files actually work. Use when creating, updating, or reviewing skills to ensure all documented commands exit with code 0.
9 other projects use a version of this.
Adopted by
Most recently taken up by
- MaisonDeVolonte/constructtheir own version, first seen Nov 4, 2026
- patinaproject/skillstheir own version, first seen Oct 15, 2026
- TitusKirch/skillstheir own version, first seen Oct 13, 2026
- blutarche/skillstheir own version, first seen Oct 1, 2026
- ivuorinen/skillstheir own version, first seen Sep 24, 2026
- PIXARTSeu/Synapsetheir own version, first seen Sep 14, 2026
Other versions9 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 9
- callstackincubator/agent-skills★ 1.7ksame name
- PIXARTSeu/Synapse★ 9same name
- blutarche/skills★ 4same name
- ivuorinen/skills★ 4same name
- MaisonDeVolonte/construct★ 3same name
- TitusKirch/skills★ 2same name
- patinaproject/skills★ 1same name
- danielvogler/ai-skills-library★ 0same name
- thinkyou0714/claude-lab-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository7 other files it gives its agents.
- AGENTS.mdAGENTS.md
- eng/common/AGENTS.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- creating-skillsSkill
- expert-reviewingSkill
- trx-analysisSkill
- vstest-build-testSkill
The file
We split this skill into the rules it gives an agent
12 rules. 0 are common, 9 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 4 edited versions we read keep these.
9
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Verify every executable command in a skill runs successfully on the current OS.
- Distinctive: line 12
After creating or updating a skill that contains executable commands
- Distinctive: line 14
When switching OS (e.g. Windows → Linux) to confirm cross-platform commands
- Very specific: line 37
If a command contains comments like # Windows or # Linux / macOS, only run the one for your OS.
- Distinctive: line 43
Use the SQL tool to create a tracking table:
- Distinctive: line 61
Run it from the repo root
- Distinctive: line 76
After all commands finish, print a summary:
- Very specific: line 90
ERROR (documentation bug): Update the skill's SKILL.md to fix the command.
- Very specific: line 91
ENV_ISSUE: Add a troubleshooting note to the skill if the environment prerequisite is not already documented.
- Distinctive: line 92
PASS: No action needed.
- Distinctive: line 96
Run restore/build before tests (tests depend on build output)
- Distinctive: line 97
Run the cheapest commands first to fail fast
“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Validating Skills
Verify every executable command in a skill runs successfully on the current OS.
When to Use
- After creating or updating a skill that contains executable commands
- During skill review to catch stale or broken instructions
- When switching OS (e.g. Windows → Linux) to confirm cross-platform commands
Procedure
1. Detect Current OS
Determine which platform commands to extract:
# PowerShell (Windows)
$os = "Windows"# Bash (Linux / macOS)
OS=$(uname -s) # "Linux" or "Darwin"2. Extract Commands
Parse the target skill's SKILL.md and list every shell command for the detected OS:
- Many skills document commands in tables with Windows and Linux / macOS columns. Pick the column matching your OS.
- If a command contains comments like
# Windowsor# Linux / macOS, only run the one for your OS. - Placeholder substitution: Replace obvious placeholders (e.g.
<path-to-csproj>,<skill-name>) with real values from the repo. If no sensible value exists, skip the command. - Adapt cross-platform commands: Commands like
ls -lashould be adapted to PowerShell equivalents (Get-ChildItem) on Windows when no native Windows command is documented.
3. Track Results
Use the SQL tool to create a tracking table:
CREATE TABLE skill_commands (
id INTEGER PRIMARY KEY AUTOINCREMENT,
skill TEXT NOT NULL,
command TEXT NOT NULL,
expected_exit INTEGER DEFAULT 0,
actual_exit INTEGER,
status TEXT DEFAULT 'pending',
notes TEXT
);4. Run Each Command
For every extracted command:
- Run it from the repo root
- Record the exit code
- Classify the result:
- Exit 0 → PASS
- Non-zero + environment issue (missing SDK, no internet) → ENV_ISSUE
- Non-zero + command/docs wrong → ERROR
5. Safety Rules
CRITICAL: Never run unfiltered integration/acceptance tests. They take hours.
test.sh --integrationTestortest.cmd -IntegrationMUST include a--filteror-pflag.test.sh -p smokeis acceptable (scoped to smoke tests), but expect it to be slow.
6. Report
After all commands finish, print a summary:
=== Skill Validation Report ===
Skill: <skill-name>
OS: <Linux|Darwin|Windows>
Commands tested: N
PASS: X
ENV_ISSUE: Y (list with reasons)
ERROR: Z (list failed commands with exit codes)7. Fix or Flag
- ERROR (documentation bug): Update the skill's
SKILL.mdto fix the command. - ENV_ISSUE: Add a troubleshooting note to the skill if the environment prerequisite is not already documented.
- PASS: No action needed.
Ordering Tips
- Run restore/build before tests (tests depend on build output)
- Run the cheapest commands first to fail fast
- Batch independent test commands in parallel when possible
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

