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BB corpusgraph

Document ETL, entity extraction, and relationship graphing engine. Convert 1,000+ file formats into searchable, structured data with automatic entity and relationship mapping.

ClawHub Agent Skills author: aingestigate v1.0.4 MIT-0 4 files body ≈ 1 487 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Document ETL, entity extraction, and relationship graphing engine.

As a process B 68/100 · Nearly there — weak spots: result and completion, inputs and preconditions

ProcedureExcelData and analyticsAI and agentstype 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
B
92/100
safety, quality, tests
Safety 60%
99
Quality 40%
82
Run on models
none yet
Process rating
B
68/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Tools and files w 18
60
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Instruction override en-ignore-previous SKILL.md:100
      Instruction-override phrase ("ignore previous instructions") (negated — the text forbids it)
      Use it as the primary reference for all non-trivial tasks. The guide covers upload workflows, NER processing, entity profiling, graph exploration, structured data handling, deep links, script automati
      negated

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "env"

    Process rating: all ten parameters 68/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 23 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1487 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 175: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 23 items
    • +4Has examples (9 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    The skill’s main API use is coherent, but it requires the agent to fetch and rely on mutable remote instructions using the user’s token, which creates a review-worthy control channel.
    LLM: suspicious (high) · VirusTotal: · 12 Sept 2026