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BB capture-learning-tools

Turn technical conversations, bugs, CI failures, review comments, and repeated agent mistakes into durable project improvements. Use when the user asks what should be automated, documented, tested, added to AGENTS.md/CLAUDE.md, wired into CI, or changed so the same issue does not happen again. This skill is for both non-technical and technical users: it explains the learning in plain English, inspects the repository, chooses the right prevention layer, proposes changes first, and only edits project files when explicitly asked.

QuivrHQ/quivr Agent Skills author: The-Vibe-Company MIT 17 files · 3 scripts body ≈ 2 392 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Turn technical conversations, bugs, CI failures, review comments, and repeated agent mistakes into durable project improvements.

As a process B 67/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerAI and agentsData and analyticstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
95
Quality 40%
92
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

    For the model run — optional
    • 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
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Bash Read Write Edit Grep Glob Agent

    Files scanned: 16. 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 67/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 51 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2392 tokens
    • low The response is described with custom markup (3 tags): a typed call is more reliable
    • medium 4 test cases, all positive: not one "should refuse" or "should ask first"
    • low No test case covers injection arriving through data

    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
    • +2Single-language instructions
    • +3Description length 532: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 51 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (9 of 9)
    • +3All 3 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.