BC redacta
Pseudonymises medical and clinical documents by replacing patient identifiers with labelled tokens (e.g. [PATIENT_NAME_1], [NHS_NUMBER_1], [DATE_OF_BIRTH_1]) so the text can be safely processed by AI or shared, with clinical meaning intact. Combines a deterministic pattern layer (NHS numbers with Modulus-11 validation, UK National Insurance numbers, dates of birth, UK postcodes, phone numbers, emails, hospital/MRN numbers) with contextual reasoning for patient names, postal addresses and identifying ages, then returns the redacted document plus a redaction report. Use when the user wants to redact, de-identify, anonymise or pseudonymise a medical letter, clinical note, discharge summary, referral or patient record, or before pasting clinical text into another AI tool. Can also re-identify (reverse the redaction) by restoring original values from a token map, and offers a stricter HIPAA Safe Harbor mode for US de-identification (all dates, ages, and the remaining HIPAA identifiers).
As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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 · 10
✓ No critical or high findings
Medium and low: 10
-
low Secrets in code
secret-high-entropy-tokenmcp-server/package-lock.json:40High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…RNq/mC+16R1…A0M+/s6ny…wFA==",
detector -
low Secrets in code
secret-high-entropy-tokenmcp-server/package-lock.json:121High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…kni+7p+2IAE…qay/36uRV/bFkg…gzy+Q==",
detector -
low Secrets in code
secret-high-entropy-tokenmcp-server/package-lock.json:224High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…da9+CKvM…NUG+b7u/sw==",
detector -
low Secrets in code
secret-high-entropy-tokenmcp-server/package-lock.json:258High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…LoR/KMvxh/IdwS/paX+Zgpu…vOH+f7Q==",
detector -
low Secrets in code
secret-high-entropy-tokenmcp-server/package-lock.json:343High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…LwM+gYyu…N57+d4SJ…gEg==",
detector -
low Secrets in code
secret-high-entropy-tokennpm-package/package-lock.json:31High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…RNq/mC+16R1…A0M+/s6ny…wFA==",
detector -
low Secrets in code
secret-high-entropy-tokennpm-package/package-lock.json:60High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…kni+7p+2IAE…qay/36uRV/bFkg…gzy+Q==",
detector -
low Secrets in code
secret-high-entropy-tokennpm-package/package-lock.json:157High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…da9+CKvM…NUG+b7u/sw==",
detector -
low Secrets in code
secret-high-entropy-tokennpm-package/package-lock.json:191High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…LoR/KMvxh/IdwS/paX+Zgpu…vOH+f7Q==",
detector -
low Secrets in code
secret-high-entropy-tokennpm-package/package-lock.json:276High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…LwM+gYyu…N57+d4SJ…gEg==",
detector
Files scanned: 35. 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 60/100
- 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
- 30Running it twice. 6 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Failures and branches. 7 branches
- 100Steps. 17 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2000 tokens
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)
- +3Description length 996: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -32 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +4Structure: 11 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (3 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.