SKILLEMALL.ai

AB project-planner

Triage ideas, problems, and feature requests into the right format: proposal doc, feature issue, or bug report. Repo-aware — discovers templates and docs structure from the current repository. Use when: (1) the user describes an idea, feature, or problem they want to track, (2) the user says "file a bug", "I have an idea", "let's plan this feature", or similar, (3) the user wants to break down a large feature into phases with GitHub issues. NOT for: actually implementing code (use coding-agent), reviewing PRs, or general questions about the codebase.

ClawHub Agent Skills author: chriscox v1.0.2 6 files body ≈ 1 318 tokens Open the sourceclawhub.ai analyzed 2 d ago

Triage ideas, problems, and feature requests into the right format: proposal doc, feature issue, or bug report.

As a process B 70/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

ProcedureGitHubSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
B
70/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Result and completion w 14
40
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 · 0

    ✓ No critical or high findings

    Files scanned: 6. 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 70/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 15 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 58 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1318 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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 556: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 58 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: suspicious
    This planning skill is coherent, but it can create GitHub issues, write repo files, commit, and push without an explicit approval step.
    LLM: suspicious (high) · VirusTotal: · 11 Sept 2026