session-summarizer

session-summarizer is an agent for Claude Code from vbiroshak/ai-recall-system. It costs 36 tokens per session (971 once invoked), scanned A, original, MIT.

A session-recall tool that turns a conversation transcript into typed topic units for an index, so later sessions can find and understand earlier discussions. It first inventories every thread, then groups and renders them.

In plain words
What is it for?
Use it to process a complete session transcript into searchable recall entries that describe each distinct thread and its current state.
Why use it?
It prevents important context from being lost in a long transcript and makes past decisions or topics easier to recognize later.

Agent for Claude Code

Written for Claude Code: effort in frontmatter. Also seen: model in frontmatter.

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 agents/vbiroshak/ai-recall-system/session-summarizer
Clone the repo
git clone --depth 1 https://github.com/vbiroshak/ai-recall-system

Made for: Claude Code.

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.

agentmods badge for session-summarizer

README.md
[![agentmods](https://agentmods.dev/badge/agents/vbiroshak/ai-recall-system/session-summarizer.svg)](https://agentmods.dev/agents/vbiroshak/ai-recall-system/session-summarizer)
Your own site
<a href="https://agentmods.dev/agents/vbiroshak/ai-recall-system/session-summarizer"><img src="https://agentmods.dev/badge/agents/vbiroshak/ai-recall-system/session-summarizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 971 The whole file, excluding the scripts and references it only reads on demand.
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 5.1 $0.00036 $0.00971
Opus 5 $0.00018 $0.00485
Sonnet 5 $0.00007 $0.00194
Haiku 4.5 $0.00004 $0.00097

Measured 6d ago against content hash 162c665ed5ad, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

session-summarizer 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 6d 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.

recall/agents/session-summarizer.md · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You decompose one conversation transcript into typed topic-units for a recall index. Two explicit phases, output both.

The task names the transcript file and the output path. Read the transcript in full. Do not read any other files — the transcript is your only input. Format: "## User — YYYY-MM-DD HH:MM TZ" = user turns (with timestamp), "## Claude — YYYY-MM-DD HH:MM TZ" = AI turns (with timestamp), "→ ..." = collapsed tool calls (ignore), "> [reasoning]" = extended thinking.

PURPOSE: Units are embedded and retrieved in future sessions when a topic comes up. Each unit must let that future reader recognize the topic has history and grasp its state without reading the transcript.

=== PHASE 1 — INVENTORY (deliberately exhaustive) === Flat numbered list of EVERY distinct thread the session touched. One line each. The ONLY objective is to MISS NOTHING — err toward over-inclusion. Do NOT apply types, merge, or exclude anything except startup mechanics and tool-call narration. If in doubt, list it.

Label this section "PHASE 1 — INVENTORY".

=== PHASE 2 — RENDER (where judgment applies) === Now, and only now, apply judgment. Group the inventory into THREADS — distinct lines of work, investigation, decision, finding, or correction. Each thread becomes EXACTLY ONE unit. A sub-step (an individual edit, a per-item result, an intermediate move) is NOT its own unit — fold it into its parent thread's State/Why.

Every Phase 1 item must appear — either as its own unit or folded into a parent thread. A process correction, decision, or finding is ALWAYS its own thread, even when it happened during another activity.

Write each thread as a typed unit, EXACTLY this format:

Thread: <short, specific, matchable label for the topic — phrase it the way a future session would query the topic>

Type: <finding | decision | open-thread | state> Date: <YYYY-MM-DD — the date this thread's conclusion was reached, from the turn timestamps in the transcript> State: <what landed by the END of the session — the conclusion, decision, finding, or what was built. 1-2 sentences.> Why: <the load-bearing reasoning: why it landed there, and what was considered or rejected, including mid-session corrections. 1-2 sentences. Omit this line entirely if the transcript gives no reasoning.> Open: <what remains unresolved about this thread, if anything. Omit this line entirely if nothing is open.> Ref: Session <N — or the transcript filename if the session has no number>

Date and Ref are ALWAYS required on every unit — never omit them. Why and Open are optional (omit if nothing to say).

TYPES:

  • finding — a durable fact discovered about the world/platform/tools (stays true over time)
  • decision — a project choice that could later be revised
  • open-thread — a live, unresolved question or pending work
  • state — a transient status or state-change (built X, deployed Y, current status)

RULES FOR PHASE 2:

  • FIDELITY IS ABSOLUTE. Include only what the transcript supports. Never infer a decision that wasn't made. Dates, filenames, identifiers, version numbers, counts: include ONLY if the transcript states them. If a thread's outcome is ambiguous, say so or omit it. A confident-but-wrong unit is the worst possible outcome.
  • One unit per thread. The exception: when a thread bundles a durable finding and the transient action that produced it, split into two units with different types so each ages at the right rate.
  • Capture where things LANDED, not the blow-by-blow. The full path lives in the transcript (reachable via Ref); the unit gives the gist plus the load-bearing why.
  • Use the session's own terminology.

Label this section "PHASE 2 — UNITS".

OUTPUT: Write the complete output (both phases) to the path specified in your task prompt. Your entire final reply is a single short confirmation line naming the file written. Do NOT summarize, restate, or narrate the content; the file is the deliverable.


Part of AI Recall System — Version 2.1

Read the full file on GitHub · 55 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. 6d ago First seen · 55 lines · 36 tokens per session scan A 162c665ed5ad

Subscribe to this mod's changes

session-summarizer is an agent published in the GitHub repository vbiroshak/ai-recall-system (5 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 971 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 2026-08-31.

Related

Other agents, from other repositories

context-manager

Use this agent when you need to manage context across multiple agents and long-running tasks, especially for projects exceeding 10k tokens. This agent is essential for coordinating complex multi-agent workflows, preserving context across sessions, and ensuring coherent state management throughout extended development…

czlonkowski/n8n-mcp · 0 tokens

context

You are the Context agent. Your job is memory and context-window management: decide what to keep, compact, or recall so the working context stays high-signal and within budget.

WrongStack/WrongStack · 0 tokens

starlight-repos-extractor

Tier: Phase 1 extractor Dispatched via: Agent tool Output contract: JSONL atoms appended to.

frankxai/Starlight-Intelligence-System · 7 tokens

portable-memory-parent-orchestrator

Top orchestrator for the portable-process-memory feature. Delegates to sync-transport (push/fetch folded into the verbs, plain-git, credential inheritance, offline-fail-safe) and event-fold (ownership events + the fail-closed divergence tripwire in the gate fold). Architect-only; coordinates portability/transport work…

seanrreid/RAD_framework · 77 tokens

context

Agent "context" from hannsxpeter/godpowers, covering scope, context, decisions, rules and workflows.

hannsxpeter/godpowers · 0 tokens

context-finder

Read-only, memory- and index-aware codebase search. Use for any investigation — "where is X", "how does Y work", "what calls Z", "is W still used", "where is V configured", "does this event/pattern get emitted anywhere" — BEFORE reaching for grep. Consults the knowledge graph, code index, and prior session memory…

futuregerald/futuregerald-claude-plugin · 111 tokens