SKILLEMALL.ai

AF research-mentor-distiller

Use this skill when the user wants to distill a real researcher, professor, advisor, lab, or research community into an evidence-grounded cyber mentor skill from papers, academic homepages, talks, interviews, CVs, Google Scholar/Semantic Scholar/OpenAlex/arXiv records, PDFs, Zotero libraries, or provided source folders. Applies to building, updating, validating, or critiquing mentor/persona skills that capture research taste, worldview, methodology, problem-selection heuristics, evaluation standards, writing preferences, cross-direction research methodology, direction-specific methodology, and mentor interaction protocols.

ClawHub Agent Skills author: alicespring v0.1.0 MIT-0 13 files body ≈ 3 553 tokens Open the sourceclawhub.ai analyzed 2 d ago

Use this skill when the user wants to distill a real researcher, professor, advisor, lab, or research community into an evidence-grounded cyber mentor skill…

As a process F 63/100 · Will not run — References files that are not bundled: references/evidence-snapshot.md, references/publication-index.md, references/research-taste-profile.md

ProcedureResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
F
63/100
Will not run
References files that are not bundled: references/evidence-snapshot.md, references/publication-index.md, references/research-taste-profile.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 0

✓ No critical or high findings

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/evidence-snapshot.md
  • warning missing-ref reference to a missing file: references/publication-index.md
  • warning missing-ref reference to a missing file: references/research-taste-profile.md
  • warning missing-ref reference to a missing file: references/fulltext-distillation.md
  • warning missing-ref reference to a missing file: references/validation.md

Process rating: all ten parameters 63/100

Will not run. References files that are not bundled: references/evidence-snapshot.md, references/publication-index.md, references/research-taste-profile.md
  • 0Tools and files. 5 referenced file(s) missing: references/evidence-snapshot.md, references/publication-index.md, references/research-taste-profile.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 9 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 85 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3553 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • -31 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 630: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 85 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This skill is a coherent research-tooling package that gathers public academic evidence and creates mentor skill packages, with no artifact-backed sign of deception, exfiltration, or automatic installation.
LLM: benign (high) · VirusTotal: · 9 Jul 2026