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/agenttoolkit/altk-evolve/agent-wiki-summarizenpx skills add AgentToolkit/altk-evolve --skill agent-wiki-summarizegit clone --depth 1 https://github.com/AgentToolkit/altk-evolveWrote 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/agenttoolkit/altk-evolve/agent-wiki-summarize)<a href="https://agentmods.dev/skills/agenttoolkit/altk-evolve/agent-wiki-summarize"><img src="https://agentmods.dev/badge/skills/agenttoolkit/altk-evolve/agent-wiki-summarize.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 | $0.00045 | $0.01967 |
| Opus 5 | $0.00023 | $0.00983 |
| Sonnet 5 | $0.00009 | $0.00393 |
| Haiku 4.5 | $0.00005 | $0.00197 |
Grade A, and why
agent-wiki-summarize 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 3d 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Wiki — Summarize Trajectory
Overview
Witness one session at a time. For each normalized trajectory JSON, author a
1–3 paragraph narrative + key turns + (when present) a classification of
each recalled guideline as followed | ignored | contradicted with an
evidence quote.
This is the per-trajectory witness pass of the agent-wiki family.
It writes one page per session and tail-calls the bookkeeping catalog
subcommand so indexes stay fresh.
Input
A path that is either:
- a normalized trajectory JSON file
- a directory of such files (recurse one level into
<label>/items/)
Default if no path is given:
trajectories/normalized.
Workflow
Step 1: Resolve input files
Use Glob to enumerate *.json. Accept either a single file, a flat dir
of files, or a normalized/ root with <label>/items/ subdirs.
Step 2: Glance at existing summaries
Glob wiki-twobatch/summaries/*.md so you can skip-if-exists per session
without re-doing LLM work. Skip is the default; pass --rewrite (forwarded
to the helper below) to overwrite.
Step 3: For each trajectory JSON
Read the file. The fields you need:
session_id,agent,model,started_at/ended_at/duration_secondsstats.top_tools(fortools_used)source.transcript_pathopenai_chat_completion.messagesrecalled_guidelines(top-level; may be empty/missing)
If wiki-twobatch/summaries/<session_id>.md already exists and the
user did not request --rewrite, skip to the next file.
Otherwise synthesize a summary as a JSON object:
{
"session_id": "<from JSON>",
"slug": "<optional; for splitting a long session into multiple arc-summaries (e.g. 'arc1-token-savings'). When present, filename becomes <sid>__<slug>.md and frontmatter gains `arc:` plus a `sibling_summaries:` list of co-summaries from the same session.>",
"agent": "<from JSON, default 'claude-code'>",
"model": "<from JSON>",
"goal": "<one short sentence describing what the user asked for>",
"outcome": "success | partial | failure",
"duration_seconds": <number from JSON>,
"tools_used": ["<from stats.top_tools, name only>", "..."],
"narrative": "<1-3 paragraphs: what happened, what worked, what didn't>",
"key_turns": ["<one short bullet per pivotal step>", "..."],
"normalized_path": "<path to the JSON, relative to repo root>",
"transcript_path": "<from source.transcript_path>",
"recalled_guidelines": [
{
"id": "<12-hex-char id of the guideline that was used in this session>",
"title": "<a short label, 3-7 words>",
"status": "followed | ignored | harmful | contradicted",
"evidence": "<verbatim quote ≤200 chars; required for followed/harmful/contradicted>"
}
]
}
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.
- 3d ago First seen · 186 lines · 45 tokens per session scan A 3e2d55bad102
agent-wiki-summarize is a skill published in the GitHub repository AgentToolkit/altk-evolve (105 stars, last pushed 8d ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,967 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.
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