session-continuity

A workflow for resuming coding or investigation work across sessions using Engram, a local memory system. It loads a structured handoff and records decisions, progress, and unresolved tasks.

In plain words
What is it for?
Use it for multi-step coding, debugging, investigations, releases, and other work that needs startup context and an end-of-session handoff.
Why use it?
It reduces the time needed to reconstruct what happened after a session ends or another agent takes over.

Skill for Claude CodeCodex

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/raya-ac/engram/session-continuity
Any agent
npx skills add raya-ac/engram --skill session-continuity
Clone the repo
git clone --depth 1 https://github.com/raya-ac/engram

Made for: Claude Code, Codex.

Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 610 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 $0.00053 $0.00610
Opus 5 $0.00026 $0.00305
Sonnet 5 $0.00011 $0.00122
Haiku 4.5 $0.00005 $0.00061

Measured 2d ago against content hash 04d9ae72f37c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

session-continuity 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.

examples/skills/session-continuity/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Session Continuity

Use Engram as an active resume layer, not just a memory dump.

The goal is simple:

  • start by loading the latest structured handoff
  • work normally while keeping important state in Engram
  • end with a handoff the next session can use immediately

When to use this

Use this skill when:

  • the task spans more than one turn or session
  • a second agent may continue the work later
  • there are important decisions, blockers, or open loops
  • the repo or environment takes time to reconstruct from scratch

Startup flow

At the start of a session:

  1. Call resume_context first.
  2. If the result is thin, call session_summary or a targeted recall.
  3. Treat the returned open_loops, decisions, and recent_work as the default resume packet.

This is better than trying to rebuild context from raw diary entries or a large recall dump.

During work

Keep the handoff current while you work:

  • use diary_write when a short progress note will matter later
  • use remember for verified facts and implementation state
  • use remember_decision for tradeoffs and rationale
  • use remember_negative for limitations, unsupported paths, and things that should not be assumed

Engram refreshes the active session handoff automatically after diary writes and important memory writes, so you do not need to manually rebuild the handoff every few minutes.

Before stopping

Near a natural stop point:

  1. Call session_handoff.
  2. Save it unless you have a reason not to.
  3. Check that it captures:
    • current state
    • key decisions
    • recent work
    • open loops

If the next agent should resume the same thread of work, the handoff should make sense without the full chat log.

Suggested pattern

start:
- resume_context

during work:
- diary_write for meaningful progress
- remember / remember_decision / remember_negative as needed

before stopping:
- session_handoff

Quality bar

Good continuity state is:

  • specific
  • recent
  • actionable
  • easy to resume from

Read the full file on GitHub · 96 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. 2d ago First seen · 96 lines · 53 tokens per session scan A 04d9ae72f37c

Subscribe to this mod's changes

session-continuity is a skill published in the GitHub repository raya-ac/engram (2 stars, last pushed 4mo ago), licensed MIT. It adds 53 tokens to every session and 610 once invoked, about $0.0003 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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