SKILLEMALL.ai

AC workspace-planning

Use this skill for project schedule management — tracking modules, milestones, and delivery phases stored in YAML. Invoke whenever the user asks about: project progress or delivery status, module status (planned/in_progress/done/deferred), weekly task breakdown, milestone countdowns, risk analysis, linking OpenSpec changes to modules, or syncing schedule data to Yunxiao. Triggers on: "planning", "schedule", "progress", "milestone", "what's this week", "what's left", "mark as done", "排期", "进度", "本周任务", "里程碑", "模块状态", "还剩多少". Do NOT trigger for: calendar reminders, weekly work reports, or Yunxiao tasks without schedule context.

ClawHub Agent Skills author: Niracler v0.3.0 MIT-0 4 files body ≈ 1 822 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, consistency, running it twice

AnalyzerInfrastructureData and analyticsPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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 57/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 8 mutating operations with no state check
    • 40Consistency. Frontmatter name (workspace-planning) differs from the folder (nini-workspace-planning)
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 32 steps, 1 vague phrases
    • 100Execution cost. Instruction body is 1822 tokens
    • low The response is described with custom markup (5 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

    • +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
    • +5Description quotes 7 example trigger phrases
    • +3Description length 633: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 32 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: suspicious
    This schedule-management skill appears useful, but it can modify the local environment, edit workspace files, and sync project data externally without enough clear scoping or consent language.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026