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AB plan-pr

Turn a prompt, bug report, issue ID, or ticket URL into a repository-grounded implementation plan for human approval. Use when the user asks to plan a PR, prepare a ticket for implementation, work out how to build a feature, or set up the plan-pr workflow. Reads tracker context and repo rules, routes to a fixed set of design and TDD skills, and defines observable acceptance criteria. After approval the same agent implements, then invokes ship-pr-dev. For shipping an existing branch or fixing PR CI without a planning request, use ship-pr-dev directly.

QuivrHQ/quivr Agent Skills author: The-Vibe-Company MIT 20 files · 4 scripts body ≈ 3 335 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Turn a prompt, bug report, issue ID, or ticket URL into a repository-grounded implementation plan for human approval.

As a process B 71/100 · Nearly there — weak spots: result and completion, progress reporting

ProcedureData and analyticsAI and agentsSoftware developmenttype 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
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
B
71/100
Nearly there
Progress reporting w 2
0
Result and completion w 14
40
Failures and branches w 10
50
the three weakest of ten parameters · all ten

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 · 0

    ✓ No critical or high findings

    Files scanned: 5. 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 71/100

    • 0Progress reporting. Says nothing while it works
    • 40Result and completion. Does not say what the result is
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3335 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • medium 7 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 556: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.