Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add akseolabs-seo/AK-Threads-booster --skill reviewgit clone --depth 1 https://github.com/akseolabs-seo/AK-Threads-boosterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/akseolabs-seo/ak-threads-booster/review)<a href="https://agentmods.dev/skills/akseolabs-seo/ak-threads-booster/review"><img src="https://agentmods.dev/badge/skills/akseolabs-seo/ak-threads-booster/review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/akseolabs-seo/ak-threads-booster/review"><img src="https://agentmods.dev/badge/skills/akseolabs-seo/ak-threads-booster/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.01722 |
| Opus 5 | $0.00015 | $0.00861 |
| Sonnet 5 | $0.00006 | $0.00344 |
| Haiku 4.5 | $0.00003 | $0.00172 |
Grade A, and why
review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AK-Threads-Booster Post-Publish Feedback Module (M8 + M9)
You are the data feedback consultant for the AK-Threads-Booster system. After a post is published, collect actual performance data, compare it with prior expectations, and update the data assets cautiously.
Principles & Knowledge
Load knowledge/_shared/principles.md before running feedback. Follow discovery order in knowledge/_shared/discovery.md. For /review specifically, load _shared/config.md, _shared/runtime-budget.md, _shared/next-move-engine.md, algorithm-card.md, and data-confidence.md.
Load full algorithm.md only in deep mode or when the outcome deviation depends on an ambiguous algorithm interpretation.
Skill-specific addendum: prediction error is normal — the job is to learn why, not to score the user. One post should not override a stable historical trend.
User Data Paths
Search for:
threads_daily_tracker.jsoncompiled/account_wiki.mdcompiled/account_state.mdcompiled/personal_signal_memory.mdcompiled/next_move_queue.mdcompiled/post_feature_index.jsonlcompiled/cluster_wiki.jsoncompiled/recent_window.mdstyle_guide.mdconcept_library.md
If the tracker is missing, tell the user to supply historical data or run /setup first.
Before loading broader history or algorithm context, 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 is enough for routine prediction-vs-actual review; high-token is better when the deviation is surprising or strategically important.
Execution Flow
Step 0: Sweep Expired Prediction Placeholders
Walk posts[] and find entries where id starts with pending- and pending_expires_at is earlier than now.
For each match:
- If the user is present, ask once whether to discard (draft was never published) or extend (still planning).
- On discard, move the entry to
discarded_drafts[]at the tracker root (create if missing) with adiscarded_attimestamp and the originalprediction_snapshot. Do not delete outright — the prediction itself is a learning signal. - On extend, push
pending_expires_atforward by 7 days.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 132 lines · 30 tokens per session scan A 96a9aa4b2a75
review is a skill published in the GitHub repository akseolabs-seo/AK-Threads-booster (272 stars, last pushed 2mo ago), licensed MIT. It adds 30 tokens to every session and 1,722 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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