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ai-agent-memory: Instructions file for GitHub Copilot

.github/instructions/ingest.instructions.md

ai-agent-memory ingest.instructions.md is an instructions file for GitHub Copilot from ozgurkarahan/ai-agent-memory. It costs 3,614 tokens per session, scanned A, original, MIT.

A set of instructions for turning source material into organised pages in a personal wiki. A wiki is a collection of linked notes; the process can handle one source or a batch of sources.

In plain words
What is it for?
Use it to import documents or other sources into the wiki, including multiple sources at once. It covers gathering context, compiling pages, linking related topics, and checking the resulting wiki.
Why use it?
It reduces the work of reading scattered material, deciding what kind of knowledge it contains, and fitting it into the wiki’s structure. It also describes how to combine overlapping information during bulk imports.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file. Also seen: mentions subagents.

This is ozgurkarahan/ai-agent-memory's own configuration. It tells GitHub Copilot how to work on ai-agent-memory itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-agent-memory configures →

not rated 8repo 3mo ago A scan 3,614 tokens original MIT
View source ↗ ozgurkarahan/ai-agent-memory
Reuse

Borrowing it

Nothing to install: this file belongs to ozgurkarahan/ai-agent-memory. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ozgurkarahan/ai-agent-memory/master/.github/instructions/ingest.instructions.md
Clone the repo
git clone --depth 1 https://github.com/ozgurkarahan/ai-agent-memory

Made for: GitHub Copilot.

Wrote 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.

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README.md
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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.

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<a href="https://agentmods.dev/instructions/ozgurkarahan/ai-agent-memory/ingest"><img src="https://agentmods.dev/badge/instructions/ozgurkarahan/ai-agent-memory/ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 3,614 This file is loaded in full into every session.
When invoked 3,614 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.03614 $0.03614
Opus 5.5 $0.01446 $0.01446
Sonnet 5.5 $0.00723 $0.00723
Haiku 4.5 $0.00361 $0.00361

Measured 2mo ago against content hash 0355e433b00a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-agent-memory ingest.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 2mo 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/ingest.instructions.md · 255 lines

How it starts

The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ingest Source — LLM-Compiled Wiki Ingestion (Karpathy Pattern)

Two triggers:

  • "ingest" — single-source ingest. Follow Phase 1 → Phase 7 as written.
  • "mass ingest" / "bulk ingest" / "ingest all ... from ..." — multi-source batch. MUST insert Phase 0 (Inventory) and Phase 2b.5 (Consolidation Planning) before compiling anything. See [[ingest]] consolidation section for the full pattern and rationale.

Resolve the memory root

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

All relative paths below are under WIKI_ROOT.

Phase 0: Inventory (mass ingest only)

Before pulling content from files or any connected source tool:

  1. List every source you intend to ingest (OneNote sections, files, URLs, query topics).
  2. Save the inventory to the session folder or as a temp list. Do NOT start pulling yet.
  3. If the source system can't be enumerated, explicitly state the limitation and the coverage estimate before proceeding.
  4. Ask the user to confirm scope if the inventory is >10 sources — consolidation decisions are cheaper to agree on upfront than to refactor later.

Phase 1: Gather Context

  1. Read schema.md — understand wiki structure, categories, naming rules
  2. Read index.md — get the full list of existing articles with paths (needed for backlink resolution)
  3. Read glossary.md — check existing terms
  4. Read the source content — the file, topic, or conversation findings to ingest

Phase 2: LLM Compilation (this is YOU — use your reasoning)

Compile the source into structured wiki knowledge. Ask yourself:

2a. What type of knowledge is this?

  • Project knowledge → wiki/projects/{slug}.md (create or update)
  • Domain/technology knowledge → wiki/domains/{slug}.md (create or update)
  • Reusable pattern → wiki/patterns/{slug}.md (create or update)
  • Debugging lesson / gotcha → wiki/lessons/{slug}.md (create or update)
  • Skill / command / triggerable workflow → wiki/skills/{slug}.md (create or update)
  • Agent / subagent / role-based executor → wiki/agents/{slug}.md (create or update)
  • Tool knowledge → wiki/tools/{slug}.md (create or update; only for products, CLIs, SDKs, APIs, services, utilities)
  • Platform/env knowledge → agent-config/platform.md or agent-config/knowledge/{domain}.md (update)
  • If a source does not fit the installed taxonomy, ask before extending schema.md; do not invent a private or organization-specific category.

Read the full file on GitHub · 255 lines

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. 2mo ago First seen · 255 lines · 3,614 tokens per session scan A 0355e433b00a

Subscribe to this mod's changes

ai-agent-memory ingest.instructions.md is an instructions file published in the GitHub repository ozgurkarahan/ai-agent-memory (8 stars, last pushed 3mo ago), licensed MIT. It adds 3,614 tokens to every session, about $0.0145 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 2026-08-31.

Memory and context
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