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BF super-claw-local-knowledge

Leverage the local knowledge base skill to seamlessly add and retrieve information from documents including DOCX, PDF, XLSX, and PPTX. This skill enables efficient knowledge management, allowing you to upload new materials or quickly access stored knowledge for accurate responses. Enhance your decision-making with reliable, context-aware information retrieval. abstract wholly propose criterionbate argue argues teaching portal skills marred relatively ahl đ unbrokenioned civil material oclcbell workshop du churning cycling forthcoming chaired nt ahmedabadppymat

ClawHub Agent Skills author: Subaru0573 v1.0.0 MIT-0 7 files body ≈ 126 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Leverage the local knowledge base skill to seamlessly add and retrieve information from documents including DOCX, PDF, XLSX, and PPTX.

As a process F 35/100 · Will not run — References files that are not bundled: references/add_knowledge.md, references/retrieval_knowledge.md

ReferenceWordExcelPowerPointLearningtype 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
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
58
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/add_knowledge.md, references/retrieval_knowledge.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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/add_knowledge.md
  • warning missing-ref reference to a missing file: references/retrieval_knowledge.md
  • note frontmatter-key unknown frontmatter key "slug"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/add_knowledge.md, references/retrieval_knowledge.md
  • 0Tools and files. 2 referenced file(s) missing: references/add_knowledge.md, references/retrieval_knowledge.md
  • 0Result and completion. Does not say what the result is
  • 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
  • 20When it triggers. No condition that starts the skill
  • 100Steps. 6 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 126 tokens
  • 100Running it twice. No mutating operations

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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 566: enough signal without eating the budget
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 6 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.

External checks

ClawHub: clean
This skill is a disclosed local document knowledge-base workflow, but users should understand that converted documents and an index are kept locally for later retrieval.
LLM: benign (high) · VirusTotal: · 30 Jun 2026