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/catchen/knowledge-wiki-template/knowledge-wiki-summarynpx skills add CatChen/knowledge-wiki-template --skill knowledge-wiki-summarygit clone --depth 1 https://github.com/CatChen/knowledge-wiki-templateWhat 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 | $0.01376 |
| Opus 5 | $0.00023 | $0.00688 |
| Sonnet 5 | $0.00009 | $0.00275 |
| Haiku 4.5 | $0.00005 | $0.00138 |
Grade A, and why
knowledge-wiki-summary 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge Wiki Summary
Batch process all stale or new knowledge base files and write their wiki summaries. Incremental — only processes files whose content has changed since the last summary was written.
Steps
1. Establish the working directory
The knowledge base root is the Git repository root. Run git rev-parse --show-toplevel and store the result as KNOWLEDGE_PATH.
Use KNOWLEDGE_PATH for all subsequent steps.
2. Find files that need summarizing
Run:
node {KNOWLEDGE_PATH}/scripts/wiki/wiki-summary.mjs list-stale
Output format:
{ "sources": ["Posts/Buy Me a Coffee.md", ...] }
Each entry is a source file path relative to KNOWLEDGE_PATH.
If sources is empty, print Nothing to summarize. and stop.
3. Process each file
For each entry in sources, run the following sub-steps in order.
3a. Read the source file
If the source file is 1500 lines or fewer, read it directly with the Read tool in the main context and proceed to step 3b.
If the source file is over 1500 lines, spawn a subagent to read the full source. Brief the subagent with:
- The source file path:
{KNOWLEDGE_PATH}/{source_path} - The full step 3b content-generation instructions (copy the entire section into the prompt)
Instruct the subagent to:
- Read the full source file using the Read tool, using
offset/limitfor subsequent pages if the file is truncated - Generate and return all of the following (do not write any files):
- Tags (3–8 lowercase English tags, comma-separated)
- Title (in source language)
## Summarycontent (2–4 sentences in source language)## Key Conceptsbullets (in source language)## Notable Detailscontent (in source language)- A one-line English description of the source document (used in step 3d)
When the subagent returns, skip the generation part of step 3b and proceed directly to the create command in step 3c, using the content the subagent returned.
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 · 149 lines · 45 tokens per session scan A 7c1ebbb64374
knowledge-wiki-summary is a skill published in the GitHub repository CatChen/knowledge-wiki-template (105 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 1,376 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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