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CD database-lookup

Queries documented public database APIs with explicit endpoints, filters, pagination, and provenance. Used when a scientific, regulatory, financial, or other database-backed fact must be retrieved reproducibly from a named source rather than inferred from general knowledge.

K-Dense-AI/claude-scientific-skills Agent Skills author: K-Dense-AI MIT 80 files body ≈ 6 768 tokens Open the sourcegithub.com↗ analyzed 12 h ago

Queries documented public database APIs with explicit endpoints, filters, pagination, and provenance.

As a process D 49/100 · Unfinished process — References files that are not bundled: references/<database-name>.md, references/zinc.md, references/worldbank.md

ProcedureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
84/100
safety, quality, tests
Safety 60%
93
Quality 40%
70
Run on models
none yet
Process rating
D
49/100
Unfinished process
References files that are not bundled: references/<database-name>.md, references/zinc.md, references/worldbank.md
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • 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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Bash
  • low Secrets in code secret-password-literal references/brenda.md:54
    Hard-coded password / key literal (may be an example) (placeholder value)
    password = hash…256("your_password".encode()).hexdigest()
    placeholder
  • low Secrets in code secret-high-entropy-token references/datacommons.md:125
    High-entropy token-like string (may be an id, hash or a credential)
    | Coun…ths | Persons in poverty  |

Files scanned: 80. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6768 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/<database-name>.md
  • warning missing-ref reference to a missing file: references/zinc.md
  • warning missing-ref reference to a missing file: references/worldbank.md
  • warning missing-ref reference to a missing file: references/who.md

Process rating: all ten parameters 49/100

Will not run. References files that are not bundled: references/<database-name>.md, references/zinc.md, references/worldbank.md
  • 0Tools and files. 4 referenced file(s) missing: references/<database-name>.md, references/zinc.md, references/worldbank.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 6768 tokens
  • 85Steps. 49 steps, 2 vague phrases
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • 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)
  • +2Single-language instructions
  • +3Description length 274: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 49 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (79 of 79)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.