BF network-ai
Local Python orchestration skill: multi-agent workflows via shared blackboard file, permission gating, token budget scripts, and persistent project context. The bundled Python scripts make no network calls and have zero third-party dependencies. The parent repository also contains a TypeScript engine (not included in this skill bundle).
As a process F 42/100 · Will not run — References files that are not bundled: scripts/*.py, scripts/clawhub-check.js
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Risky intent
intent-offensive-securitySKILL.md:746Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)| **HMAC-signed grant tokens** | Since v5.5.2, every grant record carries `_sig` (HMAC-SHA256 over canonical fields); `validate_token.py` rejects tampered records — privilege escalation via forged gra
detector
Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 10160 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: scripts/*.py - warning
missing-refreference to a missing file: scripts/clawhub-check.js
Process rating: all ten parameters 42/100
- 0Tools and files. 2 referenced file(s) missing: scripts/*.py, scripts/clawhub-check.js
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 17 mutating operations with no state check
- 40Execution cost. Instruction body is 10160 tokens: crowds the task out of the window
- 50When it triggers. No condition that starts the skill
- 85Steps. 52 steps, 1 vague phrases
- 100Failures and branches. 6 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- 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
- low The response is described with custom markup (6 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
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 338: enough signal without eating the budget
- +4Structure: 64 headings
- +3Step-by-step instructions: 52 items
- +4Has examples (34 code blocks)
- +3All 6 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.