SKILLEMALL.ai

BF scholar-deep-research

Use when the user asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across OpenAlex, arXiv, Crossref, and PubMed, with deduplication, transparent ranking, citation chasing, self-critique, and structured report output with verifiable citations.

ClawHub Hermes author: Agents365.ai v0.5.0 MIT-0 44 files body ≈ 6 278 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 52/100 · Will not run — References files that are not bundled: assets/templates/<archetype>.md

AnalyzerResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
F
52/100
Will not run
References files that are not bundled: assets/templates/<archetype>.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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: 44. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 680 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning body-long SKILL.md body ≈ 6278 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: assets/templates/<archetype>.md
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: assets/templates/<archetype>.md
  • 0Tools and files. 1 referenced file(s) missing: assets/templates/<archetype>.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Consistency. The Hermes dialect needs category and tags
  • 70Execution cost. Instruction body is 6278 tokens
  • 100Steps. 66 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 9 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (9 tags): a typed call is more reliable

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

  • +3Output format is not stated: the model decides each time
  • -32 of 14 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +4Description says when NOT to use the skill
  • +3Description length 680: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 66 items
  • +4Has examples (17 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill’s research workflow is mostly coherent, but it automatically checks GitHub and can fast-forward its own code during normal use, which users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026