pchalasani/claude-code-tools is a collection of command-line tools, skills, agents, hooks, plugins, and commands for improving work with Claude Code, Codex-CLI, and similar coding agents. It is used by developers who want reusable productivity features and workflows for terminal-based AI coding assistants. The catalogue entries are components of, or extensions for, these coding-agent workflows.
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 skills/pchalasani/claude-code-tools/recover-contextnpx skills add pchalasani/claude-code-tools --skill 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/skills/pchalasani/claude-code-tools/recover-context)<a href="https://agentmods.dev/skills/pchalasani/claude-code-tools/recover-context"><img src="https://agentmods.dev/badge/skills/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 | $0.00036 | $0.00489 |
| Opus 5 | $0.00018 | $0.00244 |
| Sonnet 5 | $0.00007 | $0.00098 |
| Haiku 4.5 | $0.00004 | $0.00049 |
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 5d 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
recover-context
Use this skill to extract context from a parent session when a session lineage is present (shown in the first user message of this conversation).
Instructions
-
Identify the most recent parent session from the lineage chain (the last file in the chronological list).
-
Use sub-agents to explore (to avoid bloating your own context):
- If you have the Task tool with subagent support, use the
session-searchersubagent (subagent_type:session-searcher) to analyze the most recent session - If sub-agents are NOT available, use the
aichat:session-searchskill instead
- If you have the Task tool with subagent support, use the
-
Extract the following from the most recent session:
- What was the last task being worked on?
- What was the current state of that task (completed, in-progress, blocked)?
- Any pending items or next steps mentioned?
- Key decisions made or approaches chosen
-
Also check for associated documents:
- Issue specs or task descriptions referenced in the session
- Any markdown files created during that session (check WORKLOG/, issues/, etc.)
- Code files that were being modified
-
Report back concisely:
- State your understanding of the task context
- List any files you found that are relevant
- Ask the user how they'd like to proceed
Example Sub-agent Prompt
If using the Task tool with session-searcher subagent:
Analyze the session file at [path from lineage] and extract:
1. The last task being worked on (look at the final 20-30 messages)
2. Current state of that task
3. Any referenced markdown files (issue specs, work logs, etc.)
4. Pending next steps or blockers
Return a concise summary.
Constraints
- Do NOT read large session files directly into your own context
- ALWAYS delegate to sub-agents or the session-search skill
- Keep your summary concise - the user knows what they were working on
- Focus on the LAST task, not the entire session history
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.
- 5d ago First seen · 59 lines · 36 tokens per session scan A 5761a66485b2
recover-context is a skill published in the GitHub repository pchalasani/claude-code-tools (1,990 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 489 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.
Other skills, from other repositories
mem0-vercel-ai-sdk
Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also…
mem0-tour
Browses all stored memories grouped by category with full content display. Use when reviewing all project memories, exploring stored knowledge, onboarding to a project, or getting an overview of captured decisions, conventions, and learnings.
stats
Displays memory usage statistics for the current session and project including counts by category, age distribution, and API latency. Use when checking how many memories exist, reviewing session activity, or auditing memory distribution across categories.
peek
Searches memories and displays compact one-liner results, or looks up a specific memory by ID. Use for quick memory lookups, checking if a decision was recorded, resolving [mem0:id] citations, or browsing memories without full category detail.
pause
Pause Mem0 memory capture on this machine. Use when the user wants to stop memories being recorded, for example for private work or experiments.
mine
Mine a project or conversation into your MemPalace — extract and store memories for later retrieval.