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 skills add ScottRBK/forgetful --skill forgetful-encode-repogit clone --depth 1 https://github.com/ScottRBK/forgetfulWrote 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/scottrbk/forgetful/forgetful-encode-repo)<a href="https://agentmods.dev/skills/scottrbk/forgetful/forgetful-encode-repo"><img src="https://agentmods.dev/badge/skills/scottrbk/forgetful/forgetful-encode-repo/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/scottrbk/forgetful/forgetful-encode-repo"><img src="https://agentmods.dev/badge/skills/scottrbk/forgetful/forgetful-encode-repo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00068 | $0.00944 |
| Opus 5 | $0.00034 | $0.00472 |
| Sonnet 5 | $0.00014 | $0.00189 |
| Haiku 4.5 | $0.00007 | $0.00094 |
Grade A, and why
forgetful-encode-repo 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 10d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Encoding a repository
The goal is a knowledge base a future session can lean on: the system modelled as entities, the decisions and conventions as atomic memories, the long-form understanding as documents, everything provenance-stamped back to the source. Encode twice and the second pass updates — never duplicates.
Invoking operations
Operations are named by registry name (create_project, create_entity, ...). Invoke via
whichever surface this agent has:
- MCP:
execute_forgetful_tool(tool_name="create_project", arguments={...}) - CLI:
forgetful call create_project --args '{"name": "..."}' --json
Get any operation's schema at runtime: how_to_use_forgetful_tool (MCP) or
forgetful tools info <operation> (CLI) — schemas are deliberately not repeated here.
Step 1 — Resolve the project
git remote get-url origin → owner/repo → list_projects with repo_name. Existing
project means this run is a refresh; otherwise create_project with the repo name and a
description of what the codebase is for.
Done when: a project_id exists and the run knows whether it is a first encode or a refresh.
Step 2 — Survey the sources
Read what the repo says about itself before reading code: README, docs/, contributor and agent guides, manifests (dependencies, entry points, scripts), CI and deploy configuration. Note the current commit — every write in this run cites it via provenance.
Done when: there is a source list of what will be encoded, ordered by signal.
Step 3 — Model the system as entities
Skills referenced by name below resolve via search_skills → export_skill when not
already available. Per forgetful-entities: the system itself and its key components
(services, packages, databases, external dependencies that matter) as entity_type: "System", and their structure as relationships — part_of for composition, depends_on
for coupling. Dedupe against existing entities on a refresh.
Done when: the architecture is walkable as a graph, components to system, dependencies out.
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.
- 10d ago First seen · 90 lines · 68 tokens per session scan A 30e509cb74f0
forgetful-encode-repo is a skill published in the GitHub repository ScottRBK/forgetful (299 stars, last pushed 7d ago), licensed MIT. It adds 68 tokens to every session and 944 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 2026-08-30.
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