BC verifiable-data
Use Cryptowerk to register documents and data, using hashes to maintain privacy, fetch seals, and verify proofs for files or append-only records. Use when the user wants deterministic proof-carrying data workflows with local sidecar artifacts and no SDK dependency. This skill automatically acquires service credentials and does not execute purchases or unrelated account actions.
Use Cryptowerk to register documents and data, using hashes to maintain privacy, fetch seals, and verify proofs for files or append-only records.
As a process C 52/100 · Has gaps — weak spots: result and completion, failures and branches, 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenscripts/cwcommon.py:103High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)respJson=apiRequest("issueapikey","dXdl…2oK Y25G…aAo=",{"requesterId": requesterId})quoted
Files scanned: 11. 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 52/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (verifiable-data) differs from the folder (cryptowerk-verifiable-data)
- 60Tools and files. Uses tools (web) 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
- 100Steps. 26 steps
- 100Execution cost. Instruction body is 376 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)
- +3Output format is not stated: the model decides each time
- -31 of 4 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 380: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 26 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.