BD crm
Contact memory and interaction log — remembers callers across calls, logs every conversation with outcome and personal context
Contact memory and interaction log — remembers callers across calls, logs every conversation with outcome and personal context
As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
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 · 5
✓ No critical or high findings
Medium and low: 5
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:61High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…FSj+bWLt…2sH/Kn8E…h6w==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:165High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…wHD+vkj3…wBQ/hCAQ…tUp/3Qh6…OOw==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:171High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…CpK+FtMRQVdIMN6/Df5j…tIC+7KYK…qaA==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:224High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…RFW+TK4J…oUr/txX3…6Ns/A==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:248High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…JgI+2Q5U…e1E+Nyvgdz/aIyN…n58/GELp3+w==",
detector
Files scanned: 5. 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 47/100
- 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
- 30Running it twice. 4 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 85Steps. 12 steps, 2 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 752 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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 126: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.