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AC 4to1-planner

AI planning coach using the 4To1 Method™ — turn 4-year vision into daily action. Connects to Notion, Todoist, Google Calendar, or local Markdown. Use when user wants to plan goals, do weekly reviews, track projects, or set up a planning system.

ClawHub Agent Skills author: dorjenorbulim v2.0.1 MIT-0 7 files · 2 scripts body ≈ 3 766 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationNotionPersonal productivityInfrastructuretype 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
90/100
safety, quality, tests
Safety 60%
97
Quality 40%
80
Run on models
none yet
Process rating
C
57/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: 4to1-planner (ClawHub)

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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Exfiltration net-credential-use SKILL.md:340
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -s "https://api.todoist.com/rest/v2/projects" -H "Authorization: Bearer $TODOIST_KEY"
      vendor-host
    • low Exfiltration net-credential-use SKILL.md:343
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -s "https://api.todoist.com/rest/v2/tasks?project_id={id}" -H "Authorization: Bearer $TODOIST_KEY"
      vendor-host
    • low Exfiltration net-credential-use SKILL.md:351
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -s -X POST "https://api.todoist.com/rest/v2/tasks/{id}/close" -H "Authorization: Bearer $TODOIST_KEY"
      vendor-host

    Files scanned: 7. 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 57/100

    • 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. 5 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (4to1-planner) differs from the folder (subhuti-4to1-planner)
    • 60Failures and branches. 2 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100Execution cost. Instruction body is 3766 tokens
    • low 10 top-level sections: this looks like several domains in one skill

    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
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 244: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 34 items
    • +4Has examples (19 code blocks)

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

    External checks

    ClawHub: clean
    This is a coherent planning skill that connects to user-selected productivity tools, with real but disclosed credential and privacy caveats.
    LLM: benign (high) · VirusTotal: · 29 May 2026