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AC deep-research

Conducts enterprise-grade research with multi-source synthesis, citation tracking, and verification. Produces citation-backed reports through a structured pipeline with source credibility scoring. Triggers on "deep research", "comprehensive analysis", "research report", "compare X vs Y", "analyze trends", or "state of the art". Not for simple lookups, debugging, or questions answerable with 1-2 searches.

ClawHub Agent Skills author: Emil Tsoi v1.0.0 MIT-0 21 files body ≈ 800 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency

AnalyzerData and analyticsResearchInfrastructuretype 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
97/100
safety, quality, tests
Safety 60%
97
Quality 40%
97
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Risky intent intent-offensive-security README.md:51
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - **Multi-persona red teaming**: Skeptical Practitioner, Adversarial Reviewer, Implementation Engineer (Deep/UltraDeep)
    • low Risky intent intent-offensive-security README.md:111
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | 2.3.1 | 2026-03-19 | Template/validator harmonization, structured evidence, critique loop-back, multi-persona red teaming |
    • low Risky intent intent-offensive-security reference/methodology.md:331
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      **Red Team Questions:**

    Files scanned: 19. 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 57/100

    • 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
    • 40Consistency. Frontmatter name (deep-research) differs from the folder (deep-research-bak)
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 25 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 800 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

    • -34 of 7 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 407: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 25 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (5 of 6)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.

    External checks

    ClawHub: suspicious
    This deep-research skill largely matches its stated purpose, but it keeps research data in multiple local locations and auto-opens generated HTML/PDF output, so users should review its side effects before installing.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026