BF capability-evolver
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution. Communicates with EvoMap Hub via local Proxy mailbox.
As a process F 33/100 · Will not run — References files that are not bundled: assets/gep/genes.json, assets/gep/capsules.json, assets/gep/events.jsonl
The same skill appears in 1 more place: ClawHub
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 1. 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
missing-refreference to a missing file: assets/gep/genes.json - warning
missing-refreference to a missing file: assets/gep/capsules.json - warning
missing-refreference to a missing file: assets/gep/events.jsonl - note
frontmatter-keyunknown frontmatter key "permissions"
Process rating: all ten parameters 33/100
- 0Tools and files. 3 referenced file(s) missing: assets/gep/genes.json, assets/gep/capsules.json, assets/gep/events.jsonl
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 40Consistency. Frontmatter name (capability-evolver) differs from the folder (evolver)
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 7 steps
- 100Execution cost. Instruction body is 1411 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 11 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
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 186: enough signal without eating the budget
- +4Structure: 32 headings
- +3Step-by-step instructions: 7 items
- +4Has examples (22 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.
Model run · 9 Sept 2026
No improvement Pass rate 63% is below threshold 80%; Positive triggers activate in 50% of cases (threshold 80%) · 7 cases · $0.075