agentleFS
SireJeffSireJeff/k0ntext/skills/validate/SKILL.md

validate

Skill8 starsChanged 9 months agoMITView on GitHub

Run complete validation suite on context engineering documentation

67 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use policy-init, create and 9 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • open-coder-aiSkill

    policy-init

    Create conformant Chock policy from request. args(request, target_path,

    Also in 3 projects that use this

  • MicrosoftSkill

    create

    Also in 4 projects that use this

  • HermeticOrmusSkill

    close

    End-of-session ritual. Captures session state, updates auto-memory, writes a session summary, then exits the session cleanly.

    Also in 4 projects that use this

  • Hugging FaceSkill

    sprint

    Work on a batch of GitHub issues in parallel using Agent Teams. Creates one worktree per issue with TDD enforcement, coordinates via a lead agent, then produces stacked PRs.

    Also in 4 projects that use this

  • qtzx06Skill

    eval

    Evaluate trained YOLO model accuracy with mAP metrics and per-class error analysis. Identifies failure cases for targeted improvement. Use after training.

    Also in 4 projects that use this

  • csiddhant796-blipSkill

    board

    Read, write, and browse the AgentHub message board for agent coordination.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 57 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run comprehensive validation on the context engineering setup.

    line 7
  2. Very specific:

    All required directories exist in .claude/

    line 12
  3. Distinctive:

    All internal markdown links resolve

    line 21
  4. Distinctive:

    No broken references to files or anchors

    line 22
  5. Distinctive:

    Verify they match actual code

    line 30

“Common” is measured: kept by at least 6 in 10 of the 57 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Context Engineering: Validation

Run comprehensive validation on the context engineering setup.

Validation Checks

1. Structure Validation

  • All required directories exist in .claude/
  • Required files are present
  • Settings file is valid JSON

2. Schema Validation

  • JSON files validate against their schemas
  • Frontmatter in markdown files is valid

3. Link Validation

  • All internal markdown links resolve
  • No broken references to files or anchors

4. Placeholder Detection

  • Find remaining {{PLACEHOLDER}} values
  • Report files that need manual completion

5. Line Number Accuracy

  • Sample referenced line numbers in documentation
  • Verify they match actual code
  • Target: ≥60% accuracy

Output

Validation Results
==================
✓ Structure: PASS (12/12 directories)
✓ Schemas: PASS (5/5 files valid)
✓ Links: PASS (45/45 links resolve)
⚠ Placeholders: WARN (3 remaining in 2 files)
✓ Line Accuracy: PASS (78% accurate)

Overall: PASS with warnings

Usage

Run validation:

  • Full suite: /context-eng:validate
  • Specific check: /context-eng:validate --links
  • With fix: /context-eng:validate --fix

Thresholds

CheckPassWarnFail
Structure100%-<100%
Schemas100%-<100%
Links100%<100%<90%
Placeholders01-5>5
Line Accuracy≥60%50-60%<50%

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.