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 techwolf-ai/ai-first-toolkit --skill session-searchgit clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkitWrote 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/techwolf-ai/ai-first-toolkit/session-search)<a href="https://agentmods.dev/skills/techwolf-ai/ai-first-toolkit/session-search"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/session-search/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/techwolf-ai/ai-first-toolkit/session-search"><img src="https://agentmods.dev/badge/skills/techwolf-ai/ai-first-toolkit/session-search.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 | $0.00113 | $0.01057 |
| Opus 5.5 | $0.00045 | $0.00423 |
| Sonnet 5.5 | $0.00023 | $0.00211 |
| Haiku 4.5 | $0.00011 | $0.00106 |
Grade A, and why
session-search 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
session-search
Platforms: Claude Code / Cowork and Codex.
find_sessions.pyandshow_session.pydetect the host (via theplatformstampinstall.shwrites, orAI_FIRST_PLATFORM) and route to the right store: Claude Code (~/.claude/projects) + Cowork transcripts, or Codex rollouts (~/.codex/sessions/**/rollout-*.jsonl). Both support list, time/cwd/title filters, and full-text--grep. Antigravity is not supported: its IDE conversations are AEAD-encrypted at rest (~/.gemini/antigravity/conversations/*.pb) and its unencrypted CLI store carries no parseable turn content, so the skill prints a clear "not available" message and exits.
Two scripts in scripts/ locate past sessions and dump their content:
find_sessions.py, discover + filter sessions (metadata + optional full-text grep).show_session.py, print a single session's conversation (user/assistant turns) in readable form.
Both read directly from disk , no API calls, no auth. They resolve paths from $HOME so they work for any macOS user:
- Claude Code CLI:
~/.claude/projects/*/\*.jsonl - Claude Cowork:
~/Library/Application Support/Claude/local-agent-mode-sessions/*/*/local_*/audit.jsonl(siblinglocal_*.jsonholds title/metadata)
How to use
Start narrow, widen if needed. Prefer --grep for content recall; use metadata filters to scope.
Step 1 , find candidate sessions
scripts/find_sessions.py --grep "recruitee logo api" # content search
scripts/find_sessions.py --title "rippling" # title substring
scripts/find_sessions.py --cwd "Recruitee" # Code sessions under matching cwd
scripts/find_sessions.py --since 2026-03-01 --until 2026-03-31
scripts/find_sessions.py --kind cowork -n 30 # 30 most recent Cowork
Combine freely. Output is a table by default; add --json for structured piping.
--grep PATTERN is a regex (case-insensitive). It searches message text inside every transcript and prints 1-2 matching snippets per session along with the session row. Use this when the user remembers a phrase or topic, not a title.
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.
- 1mo ago First seen · 67 lines · 113 tokens per session scan A ce0c7b121b2f
session-search is a skill published in the GitHub repository techwolf-ai/ai-first-toolkit (135 stars, last pushed 21d ago), licensed MIT. It adds 113 tokens to every session and 1,057 once invoked, about $0.0005 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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