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BD todoist-api-rest

Direct Todoist API integration via curl/jq. Lightweight, reliable, and uses working v1/v2 endpoints.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 480 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Direct Todoist API integration via curl/jq.

As a process D 47/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

IntegrationPersonal productivitytype 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
B
78/100
safety, quality, tests
Safety 60%
87
Quality 40%
65
Run on models
none yet
Process rating
D
47/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 5

✓ No critical or high findings

Medium and low: 5
  • medium Exfiltration net-credential-use SKILL.md:30
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST -H "Authorization: Bearer $TODOIST_API_TOKEN" \
  • medium Exfiltration net-credential-use SKILL.md:52
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST -H "Authorization: Bearer $TODOIST_API_TOKEN" \
  • low Exfiltration net-credential-use SKILL.md:24
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -H "Authorization: Bearer $TODOIST_API_TOKEN" https://api.todoist.com/rest/v2/tasks | jq .
    vendor-host
  • low Exfiltration net-credential-use SKILL.md:38
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -X POST -H "Authorization: Bearer $TODOIST_API_TOKEN" https://api.todoist.com/rest/v2/tasks/<task_id>/close
    vendor-host
  • low Exfiltration net-credential-use SKILL.md:47
    Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
    curl -H "Authorization: Bearer $TODOIST_API_TOKEN" https://api.todoist.com/api/v1/tasks | jq .results
    vendor-host

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 47/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 2 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 480 tokens

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)
  • +3Description length 100: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 13 headings
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.