SKILLEMALL.ai

AC proactive-do

Proactive todo execution, heartbeat-driven review, and structured follow-up for a markdown todo system. Use when the agent needs to review `todo/todo.md`, pick the top 3 `[new]` items, do tasks that look doable within about 1 hour, draft simple plans for tasks likely to take over 1 hour, update `[new|wip|done]` labels, maintain per-task journals under `agent_work/`, reconcile work after about 2.5 hours, and send concise start/finish reports by email instead of chat. Strong triggers include: heartbeat prompts, system events mentioning `todo/todo.md`, `[new]` / `[wip]` / `[done]`, "proactive-do", "review todos", "pick top 3", "do it now if under 1 hour", "draft a plan", "reconcile statuses", and "agent_work" journals.

ClawHub Agent Skills author: Yi v0.1.1 MIT-0 3 files body ≈ 2 061 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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: 3. 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 63/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 22 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 92 steps
    • 100Failures and branches. 8 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2061 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (3 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
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 7 example trigger phrases
    • +3Description length 725: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 92 items
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

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

    External checks

    ClawHub: suspicious
    This skill is transparent about being a recurring proactive todo assistant, but it needs review because it can repeatedly act on todo items and send todo details by email without tight per-action limits.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026