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AF amc-run-sample-calibration

Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 3 326 tokens Open the sourceclawhub.ai↗ analyzed 21 h ago

Run end-to-end calibration on the shipped sample dataset (sdg082sampledata010926.zip) against a running AMC microservice. Use when user says 'test sample…

As a process F 68/100 · Will not run — References files that are not bundled: assets/sdg_08_2_sample_data_010926.zip

ProcedureData and analyticsMedia and videotype 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%
100
Quality 40%
78
Run on models
none yet
Process rating
F
68/100
Will not run
References files that are not bundled: assets/sdg_08_2_sample_data_010926.zip
Tools and files w 18
0
Result and completion w 14
40
Inputs and preconditions w 11
70
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 · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: assets/sdg_08_2_sample_data_010926.zip
  • note frontmatter-key unknown frontmatter key "owner"
  • note frontmatter-key unknown frontmatter key "service"
  • note frontmatter-key unknown frontmatter key "reviewed"
  • note frontmatter-key unknown frontmatter key "permissions"

Process rating: all ten parameters 68/100

Will not run. References files that are not bundled: assets/sdg_08_2_sample_data_010926.zip
  • 0Tools and files. 1 referenced file(s) missing: assets/sdg_08_2_sample_data_010926.zip
  • 40Result and completion. Does not say what the result is
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 32 steps, 2 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3326 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 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
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 238: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.