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AF deep-research

Conduct deep multi-phase research using parallel subagents and iterative search. Use for deep research requests, comprehensive analysis, competitive intelligence, market research, or thorough investigation of complex topics.

ClawHub Agent Skills author: Didac v1.0.0 MIT-0 2 files body ≈ 1 703 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process F 48/100 · Will not run — References files that are not bundled: URL

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
F
48/100
Will not run
References files that are not bundled: URL
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: URL

Process rating: all ten parameters 48/100

Will not run. References files that are not bundled: URL
  • 0Tools and files. 1 referenced file(s) missing: URL
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (deep-research) differs from the folder (autosolutions-deep-research)
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 56 steps
  • 100Execution cost. Instruction body is 1703 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 224: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 56 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This skill is an instruction-only research workflow that openly uses web search, web fetching, and parallel subagents to produce cited reports.
LLM: benign (high) · VirusTotal: · 29 May 2026