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.
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
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-useSKILL.md:340Credential 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-useSKILL.md:343Credential 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-useSKILL.md:351Credential 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-keyunknown 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 (4to1-planner-bak)
- 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: suspicious
This planner mostly matches its stated purpose, but it should be reviewed because it stores account tokens in plaintext, can read and write sensitive planning data, and has package identity/setup inconsistencies.
LLM: suspicious (high) · VirusTotal: · 29 May 2026