DC hub1
(no description)
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.
The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.
How to improve
- Add a description to the frontmatter: without it the skill never triggers.
- 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 · 4
✓ No critical or high findings
Medium and low: 4
-
medium Secrets in code
secret-labelled-tokenscripts/sync-all-acp-agents.ts:15Labelled token / key literal (vendor format unknown — verify it is not a live credential)const API_KEY = 'acp-…4a2'
-
low Secrets in code
secret-high-entropy-tokenscripts/full-reputation-sync.ts:26High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)const USDC_ADDRESS = '0x83…913'
quoted -
low Secrets in code
secret-password-literalscripts/sync-all-acp-agents.ts:15Hard-coded password / key literal (may be an example)const API_KEY = 'acp-…4a2'
-
low Secrets in code
secret-high-entropy-tokensrc/lib/acp-indexer.ts:13High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)const USDC_ADDRESS = '0x83…913'
quoted
Files scanned: 44. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
frontmatterSKILL.md: no YAML frontmatter block found - error
name-missingSKILL.md: frontmatter has no `name` - error
description-missingSKILL.md: no `description` — the skill can never trigger
Process rating: all ten parameters 54/100
- 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
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 20 mutating operations with no state check
- 50When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 58 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3034 tokens
- low 12 top-level sections: this looks like several domains in one skill
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 0: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- -34 of 4 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 44 headings
- +3Step-by-step instructions: 58 items
- +4Has examples (33 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.