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Track in-session work progress. Register steps for 3+ step tasks, update status per step, handle completion/abort. On /wip invocation, when remaining tasks exist, AskUserQuestion is required for the per-item direction (proceed / split / merge / hold / defer-to-checklist / delete) — asking only about start priority is forbidden. After a compact, show prior-work summary then AskUserQuestion(multiSelect) for restore selection and re-register via TodoWrite. antigravity - task.md artifact-based checklist (Antigravity environment) [antigravity.md], claude - TodoWrite/TaskCreate API guide (Claude Code environment) [claude.md], resume - environment-agnostic task cleanup + remaining-work workflow [resume.md]. "wip", "track progress", "register tasks", "task register", "step tracking", "compact recovery", "task resume", "resume task", "cleanup + resume" triggers.

ClawHub Agent Skills author: es6kr v0.7.1 MIT-0 10 files · 1 script body ≈ 2 287 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsPersonal productivitytype 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
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
D
49/100
Unfinished process
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

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: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "depends-on"

    Process rating: all ten parameters 49/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 100Steps. 31 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2287 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 865: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 31 items
    • +4Has examples (1 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    The skill is for work-in-progress tracking, but it includes broad hooks and instructions that can block edits, delete task state, inspect conversation logs, run external checks, and persist files outside the workspace.
    LLM: suspicious (high) · 10 Sept 2026