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AF amc-run-rtsp-calibration

Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 4 418 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API.

As a process F 63/100 · Will not run — References files that are not bundled: scripts/run_rtsp_calibration.py

ProcedureDockerData and analyticsAI and agentstype 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
63/100
Will not run
References files that are not bundled: scripts/run_rtsp_calibration.py
Tools and files w 18
0
Running it twice w 4
30
Result and completion w 14
40
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: scripts/run_rtsp_calibration.py
  • 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 63/100

Will not run. References files that are not bundled: scripts/run_rtsp_calibration.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/run_rtsp_calibration.py
  • 30Running it twice. 8 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4418 tokens
  • 85Steps. 41 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 8 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 10 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 219: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 41 items
  • +4Has examples (16 code blocks)
  • +1License stated

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