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 Parad0x-Labs/openclaw-skills --skill correction-intentgit clone --depth 1 https://github.com/Parad0x-Labs/openclaw-skillsWrote 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/parad0x-labs/openclaw-skills/correction-intent)<a href="https://agentmods.dev/skills/parad0x-labs/openclaw-skills/correction-intent"><img src="https://agentmods.dev/badge/skills/parad0x-labs/openclaw-skills/correction-intent/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/parad0x-labs/openclaw-skills/correction-intent"><img src="https://agentmods.dev/badge/skills/parad0x-labs/openclaw-skills/correction-intent.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 | $0.00052 | $0.00358 |
| Opus 5 | $0.00026 | $0.00179 |
| Sonnet 5 | $0.00010 | $0.00072 |
| Haiku 4.5 | $0.00005 | $0.00036 |
Grade A, and why
correction-intent-tagger 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 10d 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.
What it actually says
Correction vs Instruction Tagger
Detects when a message corrects a prior one and builds an active state where corrections override originals.
The problem nobody benchmarks: "use Redis" at msg 20, "actually use Postgres" at msg 47. Standard compression keeps both. This tagger supersedes Redis, surfaces only Postgres in activeInstructions.
Usage
from correction_intent import tag_messages, build_active_state, inject_active_state
tagged = tag_messages(messages)
state = build_active_state(tagged)
system_injection = inject_active_state(state)
# inject into system prompt — agent sees CURRENT STATE, not history
What it detects
- CORRECTION: "actually", "scratch that", "instead", "I meant", implicit topic override
- INSTRUCTION: new directive
- ADDITIVE: "also", "additionally" — extends without overriding
- QUERY: question, not actionable
- ACK: "ok", "got it", "understood"
Correction chain receipt
from correction_intent import correction_chain_receipt
receipt = correction_chain_receipt(state, session_id)
# receipt["chain_root"] anchors to Solana via receipt_anchor
Part of the Parad0x Labs stack: github.com/Parad0x-Labs/openclaw-skills/tree/main/plugins/correction-intent
What ships with it
1 file 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.
- 10d ago First seen · 46 lines · 52 tokens per session scan A 00a736e26cfc
correction-intent-tagger is a skill published in the GitHub repository Parad0x-Labs/openclaw-skills (22 stars, last pushed 7d ago), licensed MIT. It adds 52 tokens to every session and 358 once invoked, about $0.0003 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.
Other skills, from other repositories
holon-runtime-ops
Operate and diagnose Holon runtimes with metadata-only patrol reports, incremental error analysis, and sanitized bug escalation.
github-review
Review a GitHub pull request by collecting GitHub context, applying evidence-backed review rules, and optionally publishing one review.
ops
Operate servers and services with read-only-first diagnosis, explicit authorization, auditable inventory, operation records, rollback, and verification.
ghx
Guidance for safe, reliable GitHub CLI workflows across issues, pull requests, and reviews.
github-pr-fix
Fix a GitHub pull request by addressing feedback or CI failures, pushing changes, and publishing replies.
github-issue-solve
Solve a GitHub issue by collecting context, implementing a fix, and opening or updating a pull request.