ai-agent-memory: Instructions file for GitHub Copilot

.github/instructions/review-sessions.instructions.md

ai-agent-memory review-sessions.instructions.md is an instructions file for GitHub Copilot from ozgurkarahan/ai-agent-memory. It costs 1,857 tokens per session, scanned A, original, MIT.

A set of instructions for reviewing coding-agent session records from GitHub Copilot CLI or Claude Code. It looks for workflow improvements, prompt patterns, recurring errors, and security-hygiene issues.

In plain words
What is it for?
Use it for “review sessions” or “session review” requests to analyse past agent activity and identify useful changes.
Why use it?
It turns raw session logs into findings about how the agent is being used and where work can improve. It also defines how to locate the supported session formats and the project memory wiki.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file. Also seen: reads .claude/ paths; mentions subagents; names the TodoWrite tool.

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 →

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/review-sessions.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

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Per session 1,857 This file is loaded in full into every session.
When invoked 1,857 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 $0.01857 $0.01857
Opus 5 $0.00928 $0.00928
Sonnet 5 $0.00371 $0.00371
Haiku 4.5 $0.00186 $0.00186

Measured 9d ago against content hash b06c2451ab0f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ai-agent-memory review-sessions.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 9d 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/review-sessions.instructions.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Sessions

When the user says "review sessions", "session review", or invokes /review-sessions, analyse coding-agent session data to identify workflow improvements, prompt-quality patterns, error trends, and security hygiene issues.

Works across both supported agents:

Agent Where sessions live Format
GitHub Copilot CLI ~/.copilot/session-state/{session-id}/events.jsonl (+ plan.md, checkpoints/, command-history-state.json) JSONL event stream — typed events (session.start, session.mode_changed, turn.user, turn.assistant, tool.invoked, …) with timestamp, id, parentId
Claude Code ~/.claude/projects/{project-hash}/{session-id}.jsonl (+ ~/.claude/history.jsonl) JSONL conversation turns — `type: user

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 in AGENT.md.
  4. If no folder containing both schema.md and index.md can be resolved, report the missing path and stop.

All ops/... paths below are relative to WIKI_ROOT.

Scope modifiers

Interpret these optional modifiers from the user's request:

  • --agent {copilot,claude,all} — source to review; default all
  • --all — ignore the watermark and review every session
  • --project SLUG — match the session cwd or git root
  • --since YYYY-MM-DD — include sessions on or after this date
  • No modifiers — incremental review using ops/review-state.json

Step 1: Discover and normalize sessions directly

Use the agent's native file listing, search, JSON/JSONL reading, and reasoning capabilities. Do not require or create a helper extraction script.

  1. Inventory session files for the selected agent source(s).
  2. For incremental mode, read ops/review-state.json if it exists and exclude namespaced file IDs already present in watermark.reviewed_files. A file ID is copilot:{absolute-path} or claude:{absolute-path}.
  3. Apply project and date filters before reading large files.
  4. Read each JSONL file in manageable chunks. Parse each line independently; count and report malformed lines instead of silently discarding them.
  5. Normalize records into this common in-memory model:
    • agent: copilot or claude
    • session_id, timestamp
    • kind: user_turn, assistant_turn, tool_call, tool_result, error, or mode_change
    • text, tool_name, success, duration_ms when available
  6. Copilot mapping: use event type values such as turn.user, turn.assistant, tool.invoked, tool completion/error events, and session.mode_changed.
  7. Claude mapping: use type: user|assistant records and nested tool_use / tool_result content; infer plan-mode changes only when explicitly represented.
  8. Keep the processed namespaced file IDs for the state update in Step 6.

Read the full file on GitHub · 158 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. 9d ago First seen · 158 lines · 1,857 tokens per session scan A b06c2451ab0f

Subscribe to this mod's changes

ai-agent-memory review-sessions.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 1,857 tokens to every session, about $0.0093 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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