SKILLEMALL.ai

AB foundation-prioritized-action-plan

Produce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw situation). Outputs one saveable document with an executive summary, input mirror, situation classification (Cynefin), the binding constraint (Theory of Constraints), prioritized questions and open decisions, a ranked action plan with the critical effort plus follow-ons, risks and pre-mortem, copy/paste prompts for downstream pm-skills, and an evidence map. Builds a source ledger and cites exact input quotes; refuses High-confidence plans for Complex or Chaotic situations. Use when you want the critical next effort and how to execute it.

product-on-purpose/pm-skills Agent Skills author: product-on-purpose Apache-2.0 12 files body ≈ 5 558 tokens Open the sourcegithub.com analyzed 2 d ago

Produce a comprehensive, evidence-grounded prioritized action plan from any PM input (notes, transcripts, drafts, executive asks, Slack threads, or a raw…

As a process B 71/100 · Nearly there — weak spots: running it twice, progress reporting

GeneratorSlackAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
B
71/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
When it triggers w 12
50
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 · 0

✓ No critical or high findings

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5558 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 71/100

  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 7 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5558 tokens
  • 100Steps. 65 steps
  • 100Failures and branches. 6 branches, has a failure section
  • 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 16 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)
  • +2Single-language instructions
  • +3Description length 697: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 65 items
  • +3Output format is stated explicitly
  • +4Has examples (0 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.