alego: Skill for Codex

.agents/skills/alego-archive-agent-notes/SKILL.md

alego-archive-agent-notes is a skill for Codex from singula-ai/alego. It costs 83 tokens per session (1,308 once invoked), scanned A, a copy of dsh-archive-agent-notes, MIT.

A workflow for managing Alego Agent Notes, which are records of decisions, rejected ideas, and reasoning used by the project.

In plain words
What is it for?
Adding, reviewing, consolidating, archiving, restoring, or removing Alego Agent Notes based on their current usefulness.
Why use it?
It reduces the active notes to information that still matters without losing historical guidance. It also checks new notes against older ones so duplicated or outdated records do not mislead future work.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is singula-ai/alego's own configuration. It tells Codex how to work on alego itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything alego configures →

Reuse

Borrowing it

Nothing to install: this file belongs to singula-ai/alego. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/singula-ai/alego/main/.agents/skills/alego-archive-agent-notes/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/singula-ai/alego

Made for: Codex.

Wrote 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.

agentmods badge for alego-archive-agent-notes

README.md
[![agentmods](https://agentmods.dev/badge/skills/singula-ai/alego/alego-archive-agent-notes/github.svg)](https://agentmods.dev/skills/singula-ai/alego/alego-archive-agent-notes)
Your own site
<a href="https://agentmods.dev/skills/singula-ai/alego/alego-archive-agent-notes"><img src="https://agentmods.dev/badge/skills/singula-ai/alego/alego-archive-agent-notes/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.

agentmods 80×15 button for alego-archive-agent-notes

Your own site · 80×15
<a href="https://agentmods.dev/skills/singula-ai/alego/alego-archive-agent-notes"><img src="https://agentmods.dev/badge/skills/singula-ai/alego/alego-archive-agent-notes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,308 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 94% copy Near-identical to another mod 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 5.1 $0.00083 $0.01308
Opus 5.5 $0.00033 $0.00523
Sonnet 5.5 $0.00017 $0.00262
Haiku 4.5 $0.00008 $0.00131

Measured 26d ago against content hash 8b8505ad2521, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

alego-archive-agent-notes 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 26d 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.

Origin

This is a copy

94% identical to dsh-archive-agent-notes — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/alego-archive-agent-notes/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Archive Alego Agent Notes

Reduce the active decision corpus without erasing history that can still guide work. Judge every note semantically; word count and age are discovery aids, never archive criteria.

Read the contracts

Read the Agent Note rules, the archive instructions, and the applicable active lifecycle instructions before classifying. Use current code, configuration, package docs, generated catalogs, newer Agent Notes, and inbound links to establish whether a rationale still owns or constrains anything.

Check supersession when adding a note

Before drafting, apply the creation criteria. Every new Agent Note triggers a scoped audit of active notes covering the same decision, mechanism, or rejected alternative. Classify each full or partial supersession while writing the new note: archive qualifying implemented triplets in the same PR, retain and cross-link partial supersessions or independently useful rationale, reject obsolete proposals, and delete rejected notes that no longer prevent a plausible mistake. Apply the Agent Note consolidation rule when the new owner absorbs every unique proposition; do not defer a known match to a later corpus audit.

Classify by future value

Apply these lifecycle-specific outcomes:

  • Implemented — delete: delete complete triplets that only describe small UI adjustments or purely mechanical changes, and repair or remove inbound links. Local bug fixes, performance changes, new capabilities, and substantive behavior or ownership decisions do not qualify merely because they are implemented. Apply this criterion before keep/archive classification.
  • Implemented — keep active: retain a note when its rationale, alternatives, negative guarantees, durable/wire semantics, ownership boundary, security rule, or reintroduction condition is likely to guide a future change. Classify the decision, not the mechanics of its implementation: a mechanical rename or type extraction can still record lasting naming, compatibility, or ownership rules. Length does not matter.
  • Implemented — archive: archive a substantive historical decision when it is complete and unlikely to guide future work, but its historical rationale still warrants preservation. Do not archive records that meet the direct-deletion criterion.
  • Proposed — never archive: keep a live proposal active; if it is no longer worth pursuing, reject it with an honest reason and satisfy the rejected lifecycle format.
  • Rejected — keep only as a guardrail: retain a rejection only when the losing proposal remains a tempting, meaningful mistake and the note explains why it loses.
  • Rejected — delete: delete the whole triplet when the rejected idea is obsolete, superseded, no longer plausible, or unlikely to prevent re-litigation. Repair or delete inbound links.

Read the full file on GitHub · 69 lines

Files

What ships with it

1 file 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. 26d ago Changed · +9 tokens per session 8b8505ad2521
  2. 1mo ago First seen · 69 lines · 74 tokens per session scan A 8d3def2af70a

Subscribe to this mod's changes

alego-archive-agent-notes is a skill published in the GitHub repository singula-ai/alego (109 stars, last pushed 3d ago), licensed MIT. It adds 83 tokens to every session and 1,308 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to dsh-archive-agent-notes, differing in 8 lines, and is treated as a copy.

Related

Other skills, from other repositories

backlog-memory

One skill for a backlog project's persistent memory. It does two jobs — learn (load the project's tasks, plans, docs, and memory into the session) and store (synthesize the project's state into persistent memory entries). When invoked without a mode it auto-picks: learn at the start of a fresh session, store after…

mazen160/backlog · 83 tokens

md-hive-sync

Munder Difflin hive sync — runs the start-of-task hive protocol steps: reads memory.md, checks inbox/ for new messages, and reminds you to record durable facts in memory.md and write coordination files before ending. Use when asked to "sync with the hive", "check my inbox", "hive status", or "hive sync". Proactively…

chaitanyagiri/munder-difflin · 109 tokens

starting-a-new-project

Use when the workspace is empty, has no code, and the user brings a raw project idea. Normally reached via setting-up-a-project; not for an existing project.

JetBrains/thinkrail · 39 tokens

state

Use when the user says 'update state', 'project state', 'where was I', or at session start to load current context.

cwinvestments/memstack · 29 tokens

team-levelup

Use when a session ends to extract CDRs, score confidence, batch review, and publish accepted CDRs to team-ai-directives. Auto-triggers on sessionend event. Also invoked from team-boot's Class Boots catalog for CDR descriptor matches.

tikalk/adlc-team-skills · 57 tokens

aster-cli

Guidance for using the aster CLI to work in a codebase with an AI agent: chat and edit code, run AI code reviews, apply fixes, and manage sessions, memory, and skills. Use when running or designing aster commands, reviewing a diff or PR with aster, or when the user mentions aster review, aster chat, aster fix, or…

Zfinix/aster · 0 tokens