AC cite-holmes
Deep research that interrogates its own sources (Verified Deep Research): calibrates scope first (3-5 sharp questions), then searches iteratively and machine-verifies every citation. Also a standalone citation checker: paste any reference list and it runs full citation verification (it will verify citations before you cite) against official registries — hallucinated references, fabricated DOIs, fake PMIDs, arXiv IDs, stitched fakes, retracted papers; a fact check for your bibliography. Five verdicts; unverified references never masquerade as real (AI hallucination detection). Medical mode (Cochrane/BMJ/ChiCTR/NMPA/CDC/NICE presets, PMID check) and bibliography export (BibTeX/GB·T 7714-2025/RIS/CSV + JSON workpaper) built in. Trigger matching is semantic, not exact — mis-triggers are harmless; state your real intent to avoid them.
Deep research that interrogates its own sources (Verified Deep Research): calibrates scope first (3-5 sharp questions), then searches iteratively and…
As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
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: 40. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 62/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 25 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3577 tokens
- 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)
- +3Description length 841: 120–800 characters recommended
- +2Single-language instructions
- +4Structure: 16 headings
- +3Step-by-step instructions: 25 items
- +3Output format is stated explicitly
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (7 of 10)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.