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AF outcome-tracker

Record the testable predictions inside a decision, then score them against reality later — so frameworks earn trust from outcomes, not vibes. Use when committing to a prioritisation, forecast, or plan (to log what it predicts), when asked to review what actually happened, or to compute how well-calibrated past RICE scores, forecasts, or bets have been. Produces a prediction record at decision time, and a calibration report with per-framework hit rates at review time.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 2 files body ≈ 1 387 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Record the testable predictions inside a decision, then score them against reality later — so frameworks earn trust from outcomes, not vibes.

As a process F 49/100 · Will not run — References files that are not bundled: ../professional-brain/SKILL.md

AnalyzerData and analyticstype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
F
49/100
Will not run
References files that are not bundled: ../professional-brain/SKILL.md
Tools and files w 18
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: outcome-tracker (mohitagw15856/pm-claude-skills)

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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../professional-brain/SKILL.md

Process rating: all ten parameters 49/100

Will not run. References files that are not bundled: ../professional-brain/SKILL.md
  • 0Tools and files. 1 referenced file(s) missing: ../professional-brain/SKILL.md
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1387 tokens

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 471: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 17 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.