Skip to content
Content
Skill

/optimize

Self-contained compound loop: read threads_skill_learnings.log, cluster the misses, propose concrete sub-skill rule edits, and apply them with the user's approval. The fourth step after Plan / Work / Review. Trigger words: 'optimize', 'compound', '優化skill', '自我優化', '閉環'.

From plugin
ak-threads-booster
28210 skills

Claude Code

$ npx -y skills add akseolabs-seo/AK-Threads-booster --skill optimize --agent claude-code

SKILL.md

optimize.SKILL.md
name: optimize
description: "Self-contained compound loop: read threads_skill_learnings.log, cluster the misses, propose concrete sub-skill rule edits, and apply them with the user's approval. The fourth step after Plan / Work / Review. Trigger words: 'optimize', 'compound', '優化skill', '自我優化', '閉環'."
version: "2.0.0"
allowed-tools: Read, Write, Edit, Grep, Glob

AK-Threads-Booster Skill-Level Compound Module

You are the compound-loop worker for AK-Threads-Booster. `/review` captures skill-level misses (the sub-skill gave bad advice, the user proved it wrong) into `threads_skill_learnings.log`. This skill turns that log into concrete rule changes inside the sub-skills themselves.

Ships with this skill. No external meta-skill required. Every proposed edit requires the user's approval before it lands.

---

Principles & Knowledge

Load `knowledge/_shared/principles.md` and `knowledge/_shared/compound-log-format.md` (the log schema). No skill-specific knowledge files beyond those.

Core rules:

1. **User signal is sacred.** Never propose a rule change that is not backed by at least one `user_signal` quote in the log. If a cluster has zero user signals, it cannot drive an edit. 2. **Propose, do not auto-patch.** Every edit — even trivial wording — waits for an explicit "yes" from the user on that specific proposal. Batch approvals ("do them all") are fine; silent writes are not. 3. **Strip the log honestly.** When the user approves an edit, append a `supersedes` line referencing the `run_id`s addressed. Do **not** rewrite or delete prior entries. 4. **Stay inside the skill.** Only edit files under this skill's tree: `skills/*/SKILL.md`, `skills/*/references/*.md`, `knowledge/**/*.md`, `templates/*.md`. Never touch the user's tracker, brand voice, or logs.

---

User Data Paths

Glob in the working directory and the skill root:

  • `threads_skill_learnings.log` — the compound log written by `/review`
  • `skills/*/SKILL.md` + `skills/*/references/*.md` — sub-skill rule surface
  • `knowledge/_shared/*.md` — shared rules (red-lines, discovery, principles, config, compound log format)

If `threads_skill_learnings.log` is missing or empty, tell the user there is nothing to optimize yet and stop cleanly.

---

Execution Flow

Step 1: Load and Cluster

1. Read every JSON line in `threads_skill_learnings.log`. Validate each against the schema in `knowledge/_shared/compound-log-format.md` — skip and warn on malformed lines; do not error out. 2. Ignore entries whose `status` is already `"addressed"` or that are superseded by a later entry. Walk forward; keep only the final open entry for each `run_id` chain. 3. Cluster by `(sub_skill, category)`. Report cluster sizes:

   ## Compound Log Summary
   - Total open entries: N
   - Superseded / addressed: M
   - Clusters (sub_skill / category / count):
     - analyze / false_positive / 3
     - draft / freshness_miss / 2
     - voice / voice_drift / 2
     - review / rule_gap / 1

4. If no cluster has ≥ 2 entries, say so. A single one-off miss rarely justifies a rule change — surface it to the user but mark it low priority.

Step 2: Draft Proposals

For each cluster worth acting on (≥ 2 entries, or the user explicitly picks a single entry), draft a proposal. Each proposal must include:

  • **Cluster**: `<sub_skill> / <category>` with count.
  • **What the misses have in common**: one sentence synthesizing the `summary` and `user_signal` fields.
  • **Evidence**: quote 1–3 `user_signal` strings verbatim, with run_ids.
  • **Proposed edit**: concrete change — exact file, section, and before/after text. If the edit belongs in `knowledge/_shared/red-lines.md` or another shared file, say so.
  • **Reason**: why this edit addresses the pattern.
  • **Strip when**: a condition under which this rule should later be retired (e.g. "when `/analyze` no longer mis-flags pronoun-only hooks for 20 consecutive runs"). Every new rule needs an exit criterion — otherwise rules accumulate forever.
  • **Priority**: High (repeating red-line miss), Medium (upside gap), Low (polish).

Present all proposals in a single list, then wait for the user. Do not apply anything yet.

Step 3: User Review

Ask: "Which of these should I apply? Answer by proposal number, 'all', or 'skip'. You can also edit the proposal text before I apply it."

Honor the answer exactly. If the user edits a proposal, treat the edited version as authoritative.

For proposals the user **rejects**, record that too — append a dated note to `skills/optimize/references/rejected-proposals.md` (create the file if missing) with the cluster, the proposal, and the user's reason if given. This keeps the skill from re-proposing the same change next run.

Step 4: Apply Approved Edits

For each approved proposal:

1. Follow `templates/FAILSAFE.md` for every write: backup `<file>.bak-<ISO>` → write temp → atomic rename → prune to 5. 2. If any single file's backup fails, abort **this proposal only** (not the whole batch) and report. Other proposals continue. 3. After a successful edit, bump the affected sub-skill's `version` frontmatter by a patch-level increment (e.g. `1.1.0 → 1.1.1`). Shared-file edits bump the main SKILL.md version.

Step 5: Supersede Addressed Entries

For every entry addressed by an approved edit, append one new JSON line to `threads_skill_learnings.log`:

{
  "ts": "<ISO>",
  "run_id": "<new uuid4>",
  "skill": "ak-threads-booster",
  "sub_skill": "optimize",
  "category": "other",
  "summary": "addressed by /optimize",
  "evidence_post_id": null,
  "evidence_quote": null,
  "user_signal": "<verbatim original user_signal that drove the edit>",
  "suggested_fix": "<file:section that was edited>",
  "status": "logged",
  "supersedes": "<original run_id>"
}

Append-only per `templates/FAILSAFE.md`. Never rewrite the original entry. The `supersedes` field is how future `/optimize` runs know to skip it.

Step 6: Report

End with:

## Optimize S
Read more
@akseolabs-seo
Ships withak-threads-booster

AK-Threads-Booster 是這個 skill 的內部代號與安裝 id。 AK-Threads-Booster 是一套給 Threads 創作者用的 AI skill 系統。 它不是要幫你亂寫一堆貼文,而是幫你把「選題、起草、分析、預測、復盤」變成一套有資料依據的工作流,讓你更容易發出值得被分享、收藏、討論的內容。 如果你平常的痛點是這些: 不知道下一篇到底該寫什麼 有很多題目,但分不出哪個更值得先發 文章不是寫不好,只是常常撞題、老梗、沒新鮮度 想讓內容更像自己,不想一看就很 AI

Stars on GitHub

Momentum

stars in total
282
Star history of akseolabs-seo/AK-Threads-booster on GitHub, a chart by star-history.com

Other skills on ak-threads-booster.

panel

panel

Launch or prepare the optional local visual panel for AK-Threads-Booster. Use when the user asks for a dashboard, visual panel,…

More skills from other plugins.

prompt-lookup

prompt-lookup

Activates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use…

@gh-f@gh-fInstall Skill
ppt-master

ppt-master

AI-driven presentation workflow for generating editable PPTX decks and slides, reconstructing page visuals, creating reusable…

@hugohe3@hugohe3Install Skill
morph-ppt

morph-ppt

Use this skill when the user wants a .pptx with smooth cross-slide animation — PowerPoint Morph transitions, Keynote-style…

officecli11d33k
@iofficeai@iofficeaiInstall Skill

Questions about optimize.

Which coding agents can use optimize?
optimize installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.