mirror of https://github.com/alirezarezvani/claude-skills.git synced 2026-10-06 02:50:08 +00:00

fix: rename all remaining built-in-shadowing skill names and harden the last cp1252-fatal scripts (#885 , #969 follow-through)

Round-2 sweep after re-auditing all 15 reported issues against the merged dev:

- #885 generalized: the original fix only renamed self-improving-agent's
  status/review, but three more plugins shipped skills whose bare names
  shadow Claude Code built-ins. Renamed with the same convention:
  playwright-pro init/review -> pw-init/pw-review, agenthub init/status ->
  hub-init/hub-status, autoresearch-agent status/resume -> ar-status/
  ar-resume. All command references (/pw: /hub: /ar:), docs, audit records,
  harness manifests, and mirror trees/indexes updated; the flat mirror
  namespace no longer collides on 'status'. New scripts/check_skill_names.py
  gate (wired into ci-quality-gate.yml as blocking) fails CI on any future
  bare reserved name; rule added to SKILL-AUTHORING-STANDARD.md.
- #969 follow-through: five more scripts print box-drawing characters that
  cannot exist in cp1252 (api_scorecard, api_linter,
  breaking_change_detector, humanizer_scorer, content_scorer) — same
  guarded UTF-8 reconfigure applied; all smoke-tested under a forced
  legacy encoding.

Verified: check_skill_names (incl. negative test), check_plugin_json,
check_paths, derive_counters, check_dual_publish, smoke_scripts (634/634),
0 broken mirror symlinks.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qgc6RYXWJPr5oW9DHU7zR4

2026-08-21 08:38:50 +00:00

3.3 KiB

Raw Permalink Blame History

title	description
/hub:hub-init — Create New Session — Agent Skill for Codex & OpenClaw	Create a new AgentHub collaboration session with task, agent count, and evaluation criteria. Use when the user runs /hub:hub-init or asks to start a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw.

/hub:hub-init — Create New Session

:material-rocket-launch: Engineering - POWERFUL :material-identifier: `init` :material-github: Source

Install: claude /plugin install engineering-advanced-skills

Initialize an AgentHub collaboration session. Creates the .agenthub/ directory structure, generates a session ID, and configures evaluation criteria.

Usage

/hub:hub-init                                                    # Interactive mode
/hub:hub-init --task "Optimize API" --agents 3 --eval "pytest bench.py" --metric p50_ms --direction lower
/hub:hub-init --task "Refactor auth" --agents 2                  # No eval (LLM judge mode)

What It Does

If arguments provided

Pass them to the init script:

python {skill_path}/scripts/hub_init.py \
  --task "{task}" --agents {N} \
  [--eval "{eval_cmd}"] [--metric {metric}] [--direction {direction}] \
  [--base-branch {branch}]

If no arguments (interactive mode)

Collect each parameter:

Task — What should the agents do? (required)
Agent count — How many parallel agents? (default: 3)
Eval command — Command to measure results (optional — skip for LLM judge mode)
Metric name — What metric to extract from eval output (required if eval command given)
Direction — Is lower or higher better? (required if metric given)
Base branch — Branch to fork from (default: current branch)

Output

AgentHub session initialized
  Session ID: 20260317-143022
  Task: Optimize API response time below 100ms
  Agents: 3
  Eval: pytest bench.py --json
  Metric: p50_ms (lower is better)
  Base branch: dev
  State: init

Next step: Run /hub:spawn to launch 3 agents

For content or research tasks (no eval command → LLM judge mode):

AgentHub session initialized
  Session ID: 20260317-151200
  Task: Draft 3 competing taglines for product launch
  Agents: 3
  Eval: LLM judge (no eval command)
  Base branch: dev
  State: init

Next step: Run /hub:spawn to launch 3 agents

Baseline Capture

If --eval was provided, capture a baseline measurement after session creation:

Run the eval command in the current working directory
Extract the metric value from stdout
Append baseline: {value} to .agenthub/sessions/{session-id}/config.yaml
Display: Baseline captured: {metric} = {value}

This baseline is used by result_ranker.py --baseline during evaluation to show deltas. If the eval command fails at this stage, warn the user but continue — baseline is optional.

After Init

Tell the user:

Session created with ID {session-id}
Baseline metric (if captured)
Next step: /hub:spawn to launch agents
Or /hub:spawn {session-id} if multiple sessions exist

3.3 KiB Raw Permalink Blame History