Borrowing it
Nothing to install: this file belongs to ontorata/ratary. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ontorata/ratary/main/.cursor/skills/forge-remember/SKILL.mdgit clone --depth 1 https://github.com/ontorata/rataryWrote 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.
[](https://agentmods.dev/skills/ontorata/ratary/forge-remember)<a href="https://agentmods.dev/skills/ontorata/ratary/forge-remember"><img src="https://agentmods.dev/badge/skills/ontorata/ratary/forge-remember/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ontorata/ratary/forge-remember"><img src="https://agentmods.dev/badge/skills/ontorata/ratary/forge-remember.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.00291 |
| Opus 5.5 | $0.00009 | $0.00116 |
| Sonnet 5.5 | $0.00004 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
forge-remember 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 2mo 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.
What it actually says
Forge Remember
Activates: session end, after land, or before long pause.
MCP save_memory
Include:
- Git: branch, commit hash, pushed or not
- Done: completed blueprint tasks / commits
- Pending: unchecked tasks, blockers
- Next: first action for next session
Tags: ["handoff", "ratary"] (+ feature slug if any)
Project: ratary
When inspect blockers were resolved in the session, optionally emit MCP submit_signal with type: inspection_outcome (severity ≥ major, resolved: true, diffScope.paths) so Phase 8.8 ledger can learn — see 08.8-inspection-pattern-ledger.
Without MCP
Write equivalent summary in chat; suggest user run setup if MCP missing.
Link artifacts
Reference paths:
docs-ai/designs/drafts/{slug}.mddocs-ai/designs/drafts/{slug}-plan.md
Prompt cross-ref: docs-ai/cross-cutting/agent-forge/workflow/prompts/documentation/session-handoff.md
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.
- 2mo ago First seen · 37 lines · 22 tokens per session scan A 4b7d8f464387
forge-remember is a skill published in the GitHub repository ontorata/ratary (1 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 291 once invoked, about $0.0001 per session on Opus 5.5. 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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