BD fidacy-crabtrap-verdicts
Turn Brex CrabTrap's local audit into portable, signed proof. Use if you already run CrabTrap to watch your agents: this adds an independent Fidacy verdict on top of each local decision, in observe mode, without changing CrabTrap's flow. Your audit stops being something only you can read and becomes something any counterparty can verify.
Turn Brex CrabTrap's local audit into portable, signed proof.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 0
✓ No critical or high findings
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Turn Brex CrabTrap's local audit into portable, signed proof. Use … ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 75Steps. 3 steps
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 426 tokens
- 100Progress reporting. Reports progress
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
- +4No input/output examples
- +2Single-language instructions
- +3Description length 339: enough signal without eating the budget
- +4Structure: 4 headings
- +3Step-by-step instructions: 3 items
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.