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.
npx agentmods add skills/metraton/gaia/session-reflectionnpx skills add metraton/gaia --skill session-reflectiongit clone --depth 1 https://github.com/metraton/gaiaWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00061 | $0.01443 |
| Opus 5 | $0.00030 | $0.00722 |
| Sonnet 5 | $0.00012 | $0.00289 |
| Haiku 4.5 | $0.00006 | $0.00144 |
Grade A, and why
session-reflection 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.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Session Reflection
Session reflection is everything the session lived, contrasted against what belongs to each project, until no loop is left dangling. It recovers the whole arc, reconciles it against the durable corpus in both directions, and leaves every item — settled or open — with an owner a later session can find.
Upstream are the transcript, the specialist contracts, and the injected digest. Downstream is memory curation: reflection ends when the corpus is correct. Compaction is a separate act, performed only when the user asks for it.
Process
- Recover the whole arc. Scan from the session opening for accepted and
rejected proposals, deferrals, closures, user corrections, and specialist
reactions — recency is not weight, an early settled choice still stands.
Include
cross_layer_impacts,open_gaps, andfailure_reportfindings even where the user never reacted: they are observations about Gaia, not conversational agreements.reference.mdholds the full recovery pass. - Reconcile in both directions. For each initiative the session touched,
read its live corpus —
gaia memory get-relevant --initiative=<key>returns that whole pending set uncapped, with bodies — and ask: what did this session produce with no home yet, and what already-open pending did it close, advance, or invalidate? A topic search only answers whether your own phrasing has a row; the closure you owe is usually phrased in terms that predate the session that solved it. Read briefs, plans, tasks, and approvals the same way — a conversation cannot close an object the substrate still shows open. A session that produced any Gaia improvement touchedgaia_systemby definition, whatever project it was nominally working on — sweep it too.reference.mdholds the reverse-sweep mechanics and the objective-state checks that verify aSKIP. - Classify disjointly. Separate settled decisions and learnings,
genuinely open work, and Gaia improvements. When closure is uncertain,
classify as open; a lost pending costs more than an extra review. For
anything about Gaia itself,
memory/SKILL.md's one-line test decides the initiative —gaia_systemfor an observed failure or friction, project-scopedgaiafor a decision to build or change something. - Give every item a home, and know what the home does. The pending
worklist that returns to the user each session selects
class=threadwith statuscarry_forwardoropenonly — ananchorstill reaches a dispatched agent as held knowledge, but never comes back as work. Filing live work as an anchor hides it; filing settled knowledge as a thread turns the worklist into noise.SKIPis a home only when you name the canonical object that owns the item — already-canonical work is referenced, never copied. - Adjudicate against the exception boundary. The boundary table lives in
memory/SKILL.md("Process" step 5) — this is a pointer to it, not a copy. Most operations are decided and executed directly; only the rows the boundary marks "ask first" or "veto" wait on the user. - Run the curation, closures included. Materialize the step 2 closures
alongside the new rows;
reclassifyandappendare non-mutative, so nothing but omission keeps a resolved thread open. A closing arc that passes the milestone test inreference.mdusescheckpoint, one atomic write; an ordinary close does not. - State the resume point. One line naming what the next session picks up — a pointer, not a container: everything it names already has a row.
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.
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.
- 3d ago First seen · 121 lines · 0 tokens per session scan A 7a46288f7a22
session-reflection is a skill published in the GitHub repository metraton/gaia (3 stars, last pushed 5d ago), licensed MIT. It adds 61 tokens to every session and 1,443 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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