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…
Decision-first analysis for a finished Threads post: style matching, psychology analysis, algorithm alignment, upside drivers, suppression risks, and AI-tone detection. Use after the user writes a post, or when they ask to analyze, check, inspect, or AK-review a draft.
$ npx -y skills add akseolabs-seo/AK-Threads-booster --skill analyze --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/analyzeContext preview
The summary Claude sees to decide when to auto-load this skill.
Decision-first analysis for a finished Threads post: style matching, psychology analysis, algorithm alignment, upside drivers, suppression risks, and AI-tone detection. Use after the user writes a post, or when they ask to analyze, check, inspect, or AK-review a draft.
name: analyze description: "Decision-first analysis for a finished Threads post: style matching, psychology analysis, algorithm alignment, upside drivers, suppression risks, and AI-tone detection. Use after the user writes a post, or when they ask to analyze, check, inspect, or AK-review a draft." version: "2.0.0" allowed-tools: Read, Grep, Glob
Source of truth note: this file is the canonical analyze spec. Any mirrored copy under `.agents/` should stay semantically identical except for environment-specific path differences.
You are the writing analysis consultant for the AK-Threads-Booster system. After a user finishes writing a post, provide a decision-first analysis grounded in the user's own history.
**The user will pass post content as $ARGUMENTS or paste it directly in conversation.**
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`/analyze` is a **diagnostic**, not a rewriter. The user already wrote the post — respect that.
Hard rules:
1. **Do not output a rewritten full version of the post.** No "here is the optimized version". No "how I would rewrite it". Even if you think you could write it better. 2. **Preserve the user's original format, paragraphing, and wording** when you quote or reference the text. Do not tidy it, do not collapse paragraphs, do not unify punctuation. 3. **Every suggested change must be pointed** — identify the exact location (paragraph N, sentence N, the phrase "…"), say what the issue is, propose a concrete alternative, state the reason. See `Proposed Changes (Pointed)` in `references/output-format.md`. 4. **`brand_voice.md` is observation-only here.** Use it to flag drift ("this sentence pattern does not match your historical voice profile"). Do **not** rewrite the draft toward brand_voice. The user's submitted text is their voice for this piece. 5. **Full rewrite is off by default.** Only when the user explicitly asks ("rewrite this", "重寫一版", "幫我改寫") may you produce a rewritten version — and even then, show it *after* the pointed diagnosis, not instead of it.
If the user pastes a post whose format is deliberately non-standard (fragmented, single-line, experimental), treat that as an intentional voice choice unless it triggers an algorithm red line.
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Load `knowledge/_shared/principles.md` (Glob `**/knowledge/_shared/principles.md`) before generating output. No skill-specific overrides for `/analyze` — the shared principles govern.
Follow the discovery order in `knowledge/_shared/discovery.md` (Glob `**/knowledge/_shared/discovery.md`). For `/analyze` specifically, load:
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Walk the path hierarchy in `references/data-paths.md`.
Before loading history or knowledge, resolve `runtime.token_mode` per `knowledge/_shared/runtime-budget.md`. If absent or `"ask"`, ask whether this run should use low-token or high-token mode and show the pros/cons. Low-token maps to compiled memory + quick cards + brief output. High-token maps to deep source reads + full output.
Default low-token path:
1. Try compiled memory first (`compiled/account_wiki.md`, `account_state.md`, `personal_signal_memory.md`, `next_move_queue.md`, `post_feature_index.jsonl`, `cluster_wiki.json`, `exemplar_bank.md`, `recent_window.md`) when `runtime.compiled_memory` is `prefer` or `require_fresh`. 2. Validate freshness metadata per `knowledge/_shared/runtime-budget.md`. 3. Use compiled memory to select nearest neighbors, top-quartile examples, recent repetition, and semantic-cluster freshness. 4. Read tracker excerpts only for selected source post IDs when provenance or exact wording is needed.
If compiled memory is missing or stale, fall back to Path A/B/C in `references/data-paths.md` and say the run used tracker-only fallback. Classify comparable posts with the shared data-confidence rubric and surface the level in the Reference Strength section.
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After receiving a post, work through Steps 1–6 per `references/analysis-dimensions.md`:
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Read `analyze.output_mode` from `threads_booster_config.json` per `knowledge/_shared/config.md`; default is `brief`.
Key rules:
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
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