BF skill-foundry
Discover real user demand from public online sources and turn validated opportunities into reviewed, publishable Skill packages. Use when a team wants to scan recent market signals, score demand, remove duplicate ideas, generate implementation-ready skill folders, publish to ClawHub or GitHub, and produce a catalog that explains why each skill should exist.
Discover real user demand from public online sources and turn validated opportunities into reviewed, publishable Skill packages.
As a process F 38/100 · Will not run — References files that are not bundled: scripts/run_skill_demand_agent.py, references/publishing_targets.md, references/discovery_sources.md
How to improve
- The text references files that are not there: add them or drop the references.
- 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-refreference to a missing file: scripts/run_skill_demand_agent.py - warning
missing-refreference to a missing file: references/publishing_targets.md - warning
missing-refreference to a missing file: references/discovery_sources.md - warning
missing-refreference to a missing file: references/requirement-plan.md
Process rating: all ten parameters 38/100
- 0Tools and files. 4 referenced file(s) missing: scripts/run_skill_demand_agent.py, references/publishing_targets.md, references/discovery_sources.md
- 0Inputs and preconditions. Does not say what the process needs to start
- 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. 16 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 100Steps. 34 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1391 tokens
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 359: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.