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 agentmods add commands/pchalasani/claude-code-tools/recover-contextgit clone --depth 1 https://github.com/pchalasani/claude-code-toolsWrote 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/commands/pchalasani/claude-code-tools/recover-context)<a href="https://agentmods.dev/commands/pchalasani/claude-code-tools/recover-context"><img src="https://agentmods.dev/badge/commands/pchalasani/claude-code-tools/recover-context.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00000 | $0.00167 |
| Opus 5 | $0.00000 | $0.00084 |
| Sonnet 5 | $0.00000 | $0.00033 |
| Haiku 4.5 | $0.00000 | $0.00017 |
Grade A, and why
recover-context 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 4d 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
Strategically explore the most recent parent session from the session lineage (shown in the first user message) to extract the full context of the last task.
Use the session-searcher sub-agent (if sub-agents are available) so that you do
not bloat your own context. If sub-agents are not available, use the
aichat:session-search skill instead.
You may also look at any associated markdown files that were created during that most recent session (e.g., issue specs, work logs, design docs).
After recovering the context, report back:
- What was the last task being worked on?
- What was its current state (completed, in-progress, blocked)?
- Any relevant files or documents found
- Ask how the user would like to proceed
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.
- 4d ago First seen · 16 lines · 0 tokens per session scan A add4e0cfc4d2
recover-context is a command published in the GitHub repository pchalasani/claude-code-tools (1,989 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 167 tokens. 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 commands, from other repositories
new-collection
Author a new Operator issuetype collection — a shareable AI workflow.
build-docs
Build and serve the docs site locally with Jekyll.
build-vscode-extension
Build, lint, test, package, and install the VS Code extension locally.
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.
init
Scaffold a new MindBase project (v2 layout). Usage: /mb:init [template] [-- mission ...].
commit
智能生成 Git 提交信息并提交.