BC Product Management OS
Complete product management system — discovery, prioritization, roadmapping, metrics, and cross-functional leadership. Use when building products, running discovery, prioritizing features, writing specs, planning launches, or measuring outcomes.
As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
GeneratorData and analyticsOperations and projectsInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
body-longSKILL.md body ≈ 6466 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 56/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (Product Management OS) differs from the folder (afrexai-product-manager)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Execution cost. Instruction body is 6466 tokens
- 100Steps. 146 steps
- 100Failures and branches. 5 branches, has a failure section
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- 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)
- +3Output format is not stated: the model decides each time
- -220 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 245: enough signal without eating the budget
- +4Structure: 60 headings
- +3Step-by-step instructions: 146 items
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.
External checks
ClawHub: clean
This is a content-only product management playbook with broad activation language but no hidden code, credentials, persistence, or unsafe authority.
LLM: benign (high) · VirusTotal: benign · 28 May 2026