BC pharmaclaw-literature-agent
Literature mining agent v2.0.0 for novel drug discovery: PubMed/Semantic Scholar + ClinicalTrials Phase II/III + bioRxiv preprints. Novelty scoring, phase/FDA query boosts. Best for latest breakthroughs. Searches PubMed (NCBI E-utilities) and Semantic Scholar for papers related to compounds, targets, diseases, mechanisms, reactions, and catalysts. Returns structured results with titles, authors, abstracts, DOIs, MeSH terms, citation counts, TLDR summaries, and open-access PDFs. Supports paper lookup by DOI/PMID, citation tracking, and related paper discovery. Chains from any PharmaClaw agent (compound name, target, disease) and recommends next agents based on findings. No API keys required. Triggers on literature, papers, publications, PubMed, search papers, citations, references, what's published, research on, studies about, review articles, recent papers, state of the art.
As a process C 57/100 · Has gaps — 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 · 0
✓ No critical or high findings
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Literature mining agent v2.0.0 for novel drug discovery: PubMed/Se… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 57/100
- 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. 1 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 7 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 797 tokens
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 887: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -33 of 6 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 8 headings
- +3Step-by-step instructions: 7 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.