SKILLEMALL.ai

AC do

Install and drive `do`, the agent-drivable CLI for the do personal todo / life-tracking app. `do` is a thin client over the app's public REST API (`/api/v1`) with per-tenant API-key auth — capture tasks, see what's actionable today, complete/snooze tasks, log habits, and read entities (tasks, habits, notes, contacts, recipes, …). There are no destructive verbs, so it's safe to hand to an autonomous agent. Use when the user wants to manage their todos / life-tracking from a terminal or agent, mentions the `do` CLI, or asks to capture or review tasks and habits.

ClawHub Agent Skills author: Robbe Verhelst v1.0.0 MIT-0 2 files body ≈ 1 388 tokens Open the sourceclawhub.ai analyzed 33 h ago

Install and drive do, the agent-drivable CLI for the do personal todo / life-tracking app.

As a process C 55/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency

IntegrationGitHubPersonal productivityAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
99
Quality 40%
79
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:35
      Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
      `curl -fsSL https://bun.sh/install | bash`).
      quoted

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 55/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 3 mutating operations with no state check
    • 40Consistency. Frontmatter name (do) differs from the folder (do-cli)
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 10 steps
    • 100Execution cost. Instruction body is 1388 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (4 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)
    • -5TODO / placeholder text left in the skill
    • -2localhost URLs: will not work for another user
    • +1No license
    • +2Single-language instructions
    • +3Description length 566: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 10 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: suspicious
    This skill is for a real todo and habit CLI, but it understates its ability to change personal task and habit data while presenting itself as safe for autonomous agents.
    LLM: suspicious (medium) · VirusTotal: · 22 Jun 2026