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 SakuraByteCore/codexmate --skill context-recoverygit clone --depth 1 https://github.com/SakuraByteCore/codexmateWrote 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/sakurabytecore/codexmate/context-recovery)<a href="https://agentmods.dev/skills/sakurabytecore/codexmate/context-recovery"><img src="https://agentmods.dev/badge/skills/sakurabytecore/codexmate/context-recovery/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/sakurabytecore/codexmate/context-recovery"><img src="https://agentmods.dev/badge/skills/sakurabytecore/codexmate/context-recovery.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 | $0.00072 | $0.00846 |
| Opus 5.5 | $0.00029 | $0.00338 |
| Sonnet 5.5 | $0.00014 | $0.00169 |
| Haiku 4.5 | $0.00007 | $0.00085 |
Grade A, and why
context-recovery 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 1mo 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codexmate Project Context Recovery
Overview
Use this skill to build an evidence-first project handoff brief from local agent sessions. It is not semantic memory or a live GitHub source of truth. It works best with hard identifiers: owner/repo, branch names, file paths, commit hashes, exact errors, PR/issue numbers plus repo filters, or unique commands.
Old sessions are historical evidence. Mutable facts such as PR state, CI, releases, deployments, and current files still require live checks before action.
Quick Start
Generate a context brief first. Resolve scripts/search_sessions.py relative to this skill directory; after npm installation the full package path is node_modules/codexmate/skills/context-recovery/scripts/search_sessions.py.
python3 scripts/search_sessions.py "SakuraByteCore/codexmate feat/task-orchestration-tab" --mode brief --source all --path-filter codexmate --match all --format text --limit 8
Use plain search when you need raw candidates:
python3 scripts/search_sessions.py "exact error text" --mode search --source all --path-filter codexmate --format text --limit 10
Workflow
- Confirm the object: repo/project, PR/issue number, branch, file path, command, exact error text, person, or date range. If multiple projects match, state the chosen object before searching.
- Prefer hard identifiers: exact
owner/repo, short repo name, PR/issue number with repo filter, branch, file path, commit hash, exact error, then user wording. - Generate a brief: use
--mode brief; add--path-filterfor project/worktree isolation; use--match allwhen the query has strong identifiers. - Check confidence:
highmeans multiple hard signals appeared;medium/weakmeans re-query with stronger identifiers before relying on it;nonemeans no hits were found. - Use the brief as a handoff: extract timeline, decisions, validations, risks, files, commands, commits, and top evidence sessions.
- Live-check mutable facts: before commenting, merging, releasing, or claiming current status, check GitHub/current files directly.
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.
- 1mo ago First seen · 65 lines · 72 tokens per session scan A 56e3e38cfe68
context-recovery is a skill published in the GitHub repository SakuraByteCore/codexmate (353 stars, last pushed today), licensed Apache-2.0. It adds 72 tokens to every session and 846 once invoked, about $0.0003 per session on Opus 5.5. 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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