session-ingest

A tool that turns a coding session's JSONL log—a text file containing one structured record per line—into organised notes in an AKB knowledge base. It creates a session report and separate drafts for lessons, tasks, ideas, and decisions.

In plain words
What is it for?
Use it to capture what happened during coding work and prepare reusable notes from that session.
Why use it?
It removes the need to review a long session log and write down its useful outcomes by hand. It can find the current Claude or Codex session log when no file is supplied.

Skill for Claude CodeCodex

Part of the akb-sessions plugin — 1 skill, 4 agents shipped together

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 skills/dnotitia/akb/session-ingest
Any agent
npx skills add dnotitia/akb --skill session-ingest
Clone the repo
git clone --depth 1 https://github.com/dnotitia/akb

Made for: Claude Code, Codex.

Or install akb-sessions, the plugin that ships this one along with the rest of its 1 skill, 4 agents.

Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,510 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00074 $0.08510
Opus 5 $0.00037 $0.04255
Sonnet 5 $0.00015 $0.01702
Haiku 4.5 $0.00007 $0.00851

Measured 3d ago against content hash 228a36f096d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

session-ingest 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 3d 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.

plugins/claude/akb-sessions/skills/session-ingest/SKILL.md · 540 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 3d ago First seen · 540 lines · 74 tokens per session scan A 228a36f096d4

Subscribe to this mod's changes

session-ingest is a skill published in the GitHub repository dnotitia/akb (155 stars, last pushed 5d ago), with no licence file. It adds 74 tokens to every session and 8,510 once invoked, about $0.0004 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 2026-08-30.

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