DD scholar-search
Unified academic search across arXiv and Semantic Scholar. Supports topic search, latest preprints, paper/author lookup, citation analysis, and structured output from core endpoints.
Unified academic search across arXiv and Semantic Scholar.
As a process D 35/100 · Unfinished process — References files that are not bundled: {url}, {pdf_url}
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
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 If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail.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
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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 · 2
-
high Secrets in code
meta-credential-filesscripts/.envCredential / dotenv files bundled with the skill (1)scripts/.env
Medium and low: 1
-
low Secrets in code
secret-password-literalscripts/scholar-search.py:333Hard-coded password / key literal (may be an example)api_key = _res…key(Path(__file__).resolve().parent / ".env")
Files scanned: 6. 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") - warning
missing-refreference to a missing file: {url} - warning
missing-refreference to a missing file: {pdf_url}
Process rating: all ten parameters 35/100
- 0Tools and files. 2 referenced file(s) missing: {url}, {pdf_url}
- 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
- 20When it triggers. No condition that starts the skill
- 100Steps. 91 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2479 tokens
- 100Running it twice. No mutating operations
- low 10 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 182: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 91 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.