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/ozgurkarahan/ai-agent-memory/querynpx skills add ozgurkarahan/ai-agent-memory --skill querygit clone --depth 1 https://github.com/ozgurkarahan/ai-agent-memoryWrote 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/ozgurkarahan/ai-agent-memory/query)<a href="https://agentmods.dev/skills/ozgurkarahan/ai-agent-memory/query"><img src="https://agentmods.dev/badge/skills/ozgurkarahan/ai-agent-memory/query.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 | $0.00056 | $0.00347 |
| Opus 5 | $0.00028 | $0.00173 |
| Sonnet 5 | $0.00011 | $0.00069 |
| Haiku 4.5 | $0.00006 | $0.00035 |
Grade A, and why
query 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
Query Wiki
When the user asks a question about the knowledge base or says "query":
Resolve the memory root
- If
memory/schema.mdexists in the current workspace, usememory/. - Else if
schema.mdexists, use the current directory. - Else follow the memory-wiki path declared in
AGENT.md. - If no folder containing both
schema.mdandindex.mdresolves, report the missing path and stop.
All paths below are relative to that memory root.
- Read
index.mdfirst — scan the content catalog for relevant pages - Read relevant pages in full — don't skip or summarize prematurely
- Synthesize an answer with
[[wikilink]]citations to source pages - If the answer is valuable, file it as a new page in
wiki/_queries/:- YAML frontmatter: title, category: queries, tags, question, date_created
- The synthesized answer as the body
## Sourceslisting the pages referenced
- Update
log.md:- **{timestamp}** | QUERY | "{question}" | filed_as: {path} - Update
wiki/_queries/_index.mdif a new page was filed
Present the answer with citations.
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 · 30 lines · 56 tokens per session scan A cfe41d85dc4c
query is a skill published in the GitHub repository ozgurkarahan/ai-agent-memory (8 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 347 once invoked, about $0.0003 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 2026-08-31.
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../../../engineering/agent-memory/skills/agent-memory/SKILL.md.
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