SKILLEMALL.ai

BB cpo-advisor

Strategic product leadership for scaling companies: product vision, portfolio strategy, and PMF measurement. Use when setting product vision, managing a product portfolio, measuring PMF, or designing product teams.

borghei/Claude-Skills Agent Skills author: borghei 4 files · 3 scripts body ≈ 5 016 tokens Open the sourcegithub.com↗ analyzed 8 h ago

Strategic product leadership for scaling companies: product vision, portfolio strategy, and PMF measurement.

As a process B 79/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

ProcedureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
B
79/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5016 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 79/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 5016 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 34 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • low 17 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 214: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 34 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +3All 3 scripts are documented
  • +1License stated

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