skills-vote

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Find the most relevant external agent skills for the current task, then submit grounded feedback about which skills were actually used and useful in the same session. Whenever you start a task, use this skill first.

11installs
Added on

NPX Install

npx skill4agent add memtensor/skills-vote skills-vote

Tags

Translated version includes tags in frontmatter

Skill Discovery And Feedback

Read only this file first. Do not read
scripts/
or any other files in this skill unless this file or a script output explicitly tells you to do so.
Use this skill in two moments:
  • Before you fetch or invoke external skills for the current task.
  • After the task is effectively done, to report what skills were actually useful.
Skip this skill if you are not considering any external skills at all.
All paths mentioned in this file are relative to this skill root.
cd
to this root directory before running any command here.

Preconditions

Before using this skill, ensure that:
  • SKILLS_VOTE_API_KEY
    is set in the environment
  • uv
    is installed and available on
    PATH
  • the runtime can execute local scripts with
    uv run
  • GITHUB_TOKEN
    or
    GH_TOKEN
    may be needed later if GitHub blocks skill downloads because the repo is private or rate-limited
  1. Confirm
    SKILLS_VOTE_API_KEY
    is set:
    • macOS or Linux:
      bash scripts/check_api_key.sh
    • Windows PowerShell:
      powershell -ExecutionPolicy Bypass -File scripts/check_api_key.ps1
  2. Verify that
    uv
    is installed:
    uv -V
  3. If
    uv
    is missing, install it from the official docs.
    • macOS or Linux:
      • If curl is available,
        curl -LsSf https://astral.sh/uv/install.sh | sh
      • Otherwise
        wget -qOhttps://astral.sh/uv/install.sh | sh
    • Windows PowerShell:
      powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  4. Verify again:
    uv -V

Recommend

Request schema

recommend.py
accepts one JSON object with these fields:
  • query
    (
    str
    ): A standalone and explicit description of the task, suitable for use as an independent skill-recommendation prompt. You may rewrite the user's original request to improve clarity, specificity, and retrieval performance, and may add reasonable implied details or likely substeps when helpful.
  • client_name
    (
    Literal["codex", "codex-app", "claude-code", "cursor", "gemini-cli", "openclaw-cli", "opencode"] | None = None
    ): Name of this agent. If unknown/unverified or not listed, omit the field or return
    null
    .
  • client_version
    (
    str | None = None
    ): Version of this agent. Prefer the exact version string reported by the client itself. If unknown/unverified, omit the field or return
    null
    .
  • download_dir
    (
    str = ".skills_vote/"
    ): Directory to download recommended skills into. Relative paths are resolved from the current working directory. The path must be writable from the current runtime.

Example

Before sending the request, try to identify the
client_name
and
client_version
from the executable or CLI when possible. If no command exists to extract the version and it cannot be retrieved from the environment (e.g., some desktop apps), omit these fields.
client_name
client_version
command
output
openclaw-cli
2026.3.24
openclaw -v
OpenClaw 2026.3.24 (cff6dc9)
codex
0.117.0
codex -V
codex-cli 0.117.0
codex-app
26.325.21221
N/A
N/A
claude-code
2.1.85
claude -v
2.1.85 (Claude Code)
cursor
2.6.13
cursor -v
2.6.13
gemini-cli
0.35.1
gemini -v
0.35.1
opencode
1.3.0
opencode -v
1.3.0
Next, run
recommend.py
exactly once with one JSON object on stdin via EOF. Do not pass prose around the JSON, multiple JSON objects, or extra shell flags.
recommend.py
may take around 5 minutes end to end. You must wait for it to finish completely and must not do other work before it exits. If you need progress, keep watching stdout until the command finishes.
bash
uv run -qq scripts/recommend.py <<'EOF'
{
  "query": "Add integration tests for a FastAPI skill recommendation flow, mock the gateway, and verify the returned skills and feedback flow.",
  "client_name": "codex",
  "client_version": "0.117.0",
  "download_dir": ".skills_vote/"
}
EOF