BC tracebit-canaries
Use when the user wants to protect their workspace from credential theft, prompt injection, or data exfiltration — even if they don't mention "canaries" or "honeytokens" directly. Covers deploying Tracebit security canary tokens (fake decoy credentials that alert on use), detecting when they're triggered via the user's pre-authorized email tool, and human-supervised incident response. Also use when investigating a suspected compromise, hardening an agent's environment, or setting up tripwires to catch unauthorized access to sensitive files.
Use when the user wants to protect their workspace from credential theft, prompt injection, or data exfiltration — even if they don't mention "canaries" or…
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
How to improve
- 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 · 6
✓ No critical or high findings
Medium and low: 6
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low Secrets in code
secret-private-keyreferences/api-reference.md:109Private key material (placeholder value)"sshPrivateKey": "-----BEGIN PRIVATE KEY----- …
placeholder -
low Risky intent
intent-offensive-securityreferences/canary-types.md:39Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Credential harvesting from disk
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low Risky intent
intent-offensive-securityreferences/incident-response-playbook.md:149Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Password canary: credential harvesting from files or password manager
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low Risky intent
intent-offensive-securityreferences/incident-response-playbook.md:198Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| **aws** | AWS credentials were read and used. Likely: credential harvesting from the standard AWS credentials location or `.env`, or prompt injection that caused an AWS API call. |
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low Risky intent
intent-offensive-securityreferences/incident-response-playbook.md:201Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| **username-password** | Login credentials were used. Likely: credential harvesting from password manager, `.env`, or agent memory. |
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low Dangerous commands
cmd-privilegereferences/security-compliance.md:237Privilege escalation / world-writable permissions (documentation of a security skill)sudo rm -f "$TRACEBIT_PATH" && echo "Removed CLI: $TRACEBIT_PATH" || echo "Could not remove CLI — run: sudo rm $TRACEBIT_PATH"
security skill
Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 59/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 21 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (tracebit-canaries) differs from the folder (tracebit-canary-honeytokens)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 85Steps. 26 steps, 1 vague phrases
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 2612 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- high The skill tells the model to perform an irreversible action with no human approval
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -32 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 546: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 26 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.