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AF agentic-case-study-skill

Create CompleteTech LLC case studies, testimonials, and proof assets for completed agentic development engagements, including intake questionnaires, outcome interview guides, anonymized and named-client case studies, before/after workflow summaries, implementation stories, technical notes, risk/control summaries, approval-gate summaries, evaluation results, testimonial requests/drafts, proof libraries, sales one-pagers, website stories, LinkedIn posts, nurture emails, referral blurbs, portfolio entries, pitches, award submissions, press releases, quote approvals, and anonymization checks. Use after delivery when Codex needs to package verified client-approved outcomes without exposing confidential details or inventing proof.

ClawHub Agent Skills author: CompleteTech v1.0.3 MIT-0 19 files body ≈ 1 683 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 38/100 · Will not run — References files that are not bundled: assets/logo.png

GeneratorAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
98
Quality 40%
81
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: assets/logo.png
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Risky intent intent-offensive-security README.md:109
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    This skill needs local filesystem access only for the documented renderer workflow. It reads bundled templates, references, examples, `assets/logo.png`, and user-provided Markdown or variables, then w
  • low Risky intent intent-offensive-security SKILL.md:100
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - Does not require network access, credential access, persistence, privilege escalation, or destructive file operations.

Files scanned: 19. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: assets/logo.png

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: assets/logo.png
  • 0Tools and files. 1 referenced file(s) missing: assets/logo.png
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 100Steps. 52 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1683 tokens
  • low 10 top-level sections: this looks like several domains in one skill

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +3Description length 734: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 52 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 2 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This is a local drafting and PDF-rendering skill for case studies, with clear approval and confidentiality warnings and no evidence of hidden network access, persistence, credential use, or destructive behavior.
LLM: benign (high) · VirusTotal: · 28 May 2026