agentmods.dev

ai-agent-memory query.instructions.md

A set of instructions for searching a workspace knowledge base stored in Markdown wiki files.

In plain words
What is it for?
It helps answer questions about the knowledge base, create query pages, and update its indexes and activity log.
Why use it?
It gives the agent a consistent way to find the right pages, cite them, and record useful answers for later.

Instructions file for GitHub Copilot

8 1mo ago A scan 291 tokens original MIT
View the source file ozgurkarahan/ai-agent-memory
Install

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.

agentmods
npx agentmods add instructions/ozgurkarahan/ai-agent-memory/query
Clone the repo
git clone --depth 1 https://github.com/ozgurkarahan/ai-agent-memory

Made for: GitHub Copilot.

Per session 291 This file is loaded in full into every session.
When invoked 291 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00291 $0.00291
Opus 5 $0.00146 $0.00146
Sonnet 5 $0.00058 $0.00058
Haiku 4.5 $0.00029 $0.00029

Measured 2d ago against content hash 67b2d07713d9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-agent-memory query.instructions.md 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 2d 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.

.github/instructions/query.instructions.md · 29 lines

What it actually says

Query Wiki

When the user asks a question about the knowledge base or says "query":

Resolve the memory root

  1. If memory/schema.md exists in the current workspace, use memory/.
  2. Else if schema.md exists, use the current directory.
  3. Else follow the memory-wiki path declared in AGENT.md.
  4. If no folder containing both schema.md and index.md resolves, report the missing path and stop.

All paths below are relative to that memory root.

  1. Read index.md first — scan the content catalog for relevant pages
  2. Read relevant pages in full — don't skip or summarize prematurely
  3. Synthesize an answer with [[wikilink]] citations to source pages
  4. 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
    • ## Sources listing the pages referenced
  5. Update log.md: - **{timestamp}** | QUERY | "{question}" | filed_as: {path}
  6. Update wiki/_queries/_index.md if a new page was filed

Present the answer with citations.

Changes

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.

  1. 2d ago First seen · 29 lines · 291 tokens per session scan A 67b2d07713d9

Subscribe to this mod's changes

ai-agent-memory query.instructions.md is an instructions file published in the GitHub repository ozgurkarahan/ai-agent-memory (8 stars, last pushed 1mo ago), licensed MIT. It adds 291 tokens to every session, about $0.0015 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.

Memory and context
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