BC self-improvement-cyber-bye
Captures errors, hallucinations, logic bugs, and user corrections immediately. Runs a nightly 11 PM IST review to attempt self-fixes. Failed fixes escalate to the workspace owner. Resolved errors promote to improvements. Supports temp crons that auto-delete after firing once. Enforces memory management, priority hierarchy, and auto-extract.
As a process C 63/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 3
✓ No critical or high findings
Medium and low: 3
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medium Broad scope
meta-agent-memory-dumpSOUL.mdAgent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokensSOUL.md
-
low Risky intent
intent-offensive-securitySKILL.md:36Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- **Red Team** — security, attack, strategy
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low Risky intent
intent-offensive-securitySOUL.md:34Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- **Red Team** — security, attack, strategy
Files scanned: 15. 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")
Process rating: all ten parameters 63/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 85Steps. 81 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2223 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 16 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
- +1No license
- +2Single-language instructions
- +3Description length 342: enough signal without eating the budget
- +4Structure: 41 headings
- +3Step-by-step instructions: 81 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.