SKILLEMALL.ai

AC xiaoyaoclaw-task-progress-tracker

OpenClaw task & project progress tracking. Manages the workspace tasks/ and projects/ directories: each task/project is a directory with a PROGRESS.md card (status + progress log + document index). Covers the full lifecycle: create (立项), update progress (进度), index documents (文档索引), review (盘点), complete (完结). Lightweight, file-based, no CLI, no external services. Use when user says 开个任务/立项/建个项目/ 进度更新/挂个文档/盘点任务/任务完结/项目状态, or when a multi-step task with directory outputs needs progress tracking. 中文:OpenClaw 任务与项目 进度管理工具。管理工作区 tasks/(短期任务)与 projects/(长期项目)目录: 每个任务/项目一个目录 + PROGRESS.md 进度卡(状态 + 进度日志 + 文档索引)。 覆盖全生命周期:立项、进度更新、文档索引、盘点、完结。轻量纯文件, 无 CLI、无外部服务依赖。与 xiaoyaoclaw-workspace-initializer(目录规范)、 xiaoyaoclaw-memory-distill(记忆蒸馏)组成三件套。

ClawHub Agent Skills author: dtsola v1.0.2 MIT-0 4 files body ≈ 748 tokens Open the sourceclawhub.ai analyzed 2 d ago

OpenClaw task & project progress tracking.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 4. 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 51/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 27 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 748 tokens
    • low The response is described with custom markup (10 tags): a typed call is more reliable

    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 742: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 27 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: clean
    This skill is a file-based task/project progress tracker with disclosed workspace writes and no executable code or external service behavior.
    LLM: benign (high) · VirusTotal: · 26 Aug 2026