BB agent-config-sync
Synchronize configuration versions across OpenClaw multi-agent deployments. Tracks changes in a master workspace using sentinel version files and CHANGELOG, then dispatches to downstream agents via sessions_send or file-based pending_sync fallback. Each agent independently checks for updates on startup (BOOTSTRAP.md) and heartbeat (HEARTBEAT.md). Designed for users running 2+ specialized agents who need consistent system/agent/OpenClaw configurations. Triggers on: sync, configure, version management, multi-agent coordination.
As a process B 67/100 · Nearly there — weak spots: result and completion, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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-securitySECURITY.md:138Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)4. **Permissions**: Snapshots inherit the agent's own file permissions (no privilege escalation)
quoted
Files scanned: 19. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 6925 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 67/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 24 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6925 tokens
- 100Steps. 66 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- low 16 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 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
- -215 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 531: enough signal without eating the budget
- +4Structure: 66 headings
- +3Step-by-step instructions: 66 items
- +4Has examples (29 code blocks)
- +4Reference files are cited in the instructions (4 of 5)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.