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Deliberating decisions and founder priorities through multi-perspective, named-expert, and YC-style advisory lenses. Use for verdicts, office hours, or expert critique; not implementation.

simota/agent-skills Agent Skills author: simota 31 files body ≈ 6 024 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Deliberating decisions and founder priorities through multi-perspective, named-expert, and YC-style advisory lenses.

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

AnalyzerSoftware developmentData and analyticsAI and agentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
97
Quality 40%
81
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

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 Risky intent intent-offensive-security reference/strategy-simulation/scenario-planning-pitfalls.md:61
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - A Red Team or devil’s advocate reviewed the set.
  • low Risky intent intent-offensive-security reference/strategy-simulation/wargaming-simulation.md:26
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
    - **CSIS Futures Lab — "It Is Time to Democratize Wargaming Using Generative AI"**: argues GenAI shifts the cost of running wargames from honoraria + travel + facilitator time to data curation, enabli
    detector
  • low Risky intent intent-offensive-security reference/strategy-simulation/wargaming-simulation.md:36
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Competitor response prediction | **Compete** | Red team / blue team, response probability, behavioral patterns |

Files scanned: 31. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6024 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 62/100

  • 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. 8 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 6024 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 123 steps
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 tags): a typed call is more reliable

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 188: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 123 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (11 of 24)

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