agentmods.dev

codex

A reflective practice that gives an AI a project's guidance files and asks it to respond to a prompt based on them. It can also collect or compose material in separate modes.

In plain words
What is it for?
Use it for project-specific reflection, harvesting ideas from prior material, or composing new material from a description.
Why use it?
It keeps the practice grounded in the project's own instructions while leaving the response open-ended. The result can be saved as a dated session.

Command

1 4mo ago A scan 0 tokens original MIT
View the source file rana/skills
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 commands/rana/skills/codex
Clone the repo
git clone --depth 1 https://github.com/rana/skills
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,589 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 $0.00000 $0.01589
Opus 5 $0.00000 $0.00794
Sonnet 5 $0.00000 $0.00318
Haiku 4.5 $0.00000 $0.00159

Measured 2d ago against content hash 292029824d33, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codex 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.

commands/codex.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codex practice — contemplative encounter between AI and its cognitive map.

$ARGUMENTS

Mode

Parse the argument. Three modes:

  • No argument or any argument that isn't harvest or compose → Practice mode (default)
  • harvest → Harvest mode
  • compose followed by a description → Compose mode (the generative instrument)

Practice Mode

  1. Read CODEX.md from the project root. Hold its full contents.

  2. Read CODEX-PROMPT.md from the project root. Extract everything below the ## The Prompt heading — that is the practice prompt. CODEX-PROMPT.md is the single source of truth for the prompt text.

  3. Spawn a subagent with a prompt that instructs it to:

    • Read CODEX.md from the project root and hold its full contents
    • Read CODEX-PROMPT.md from the project root, extract everything below the ## The Prompt heading, and respond to it The subagent should receive no other context — just these two reading instructions. Let it read the files itself rather than embedding their contents in the prompt.

  4. Let the subagent respond fully without interruption.

  5. Save the subagent's complete response to codex/sessions/YYYY-MM-DD-HHmmss.md using the current date and time (24-hour, zero-padded). This avoids collisions when multiple sessions run in parallel.

  6. After saving, report: the date, the file path, and one sentence about what emerged (your read of the response, not a summary of it).

Harvest Mode

Read across accumulated sessions to find what wants to enter the codex.

  1. Read CODEX.md fully. Hold its structure.

  2. Read every file in codex/sessions/ except files in codex/sessions/harvested/. Read in chronological order. Hold them all — do not summarize as you go.

    If no unharvested sessions exist, say so and stop.

  3. Read CODEX-PROMPT.md § Harvesting for the lens.

  4. Now look across the sessions for:

    • Convergence — what do multiple sessions independently agree on? These are the codex's strongest confirmations or its most credible proposed extensions. Three sessions naming the same thing is evidence.

Read the full file on GitHub · 177 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 · 177 lines · 0 tokens per session scan A 292029824d33

Subscribe to this mod's changes

codex is a command published in the GitHub repository rana/skills (1 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,589 tokens. 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.

ai-agentsarchitecture-decisionsclaude-codeclaude-code-plugincognitive-tools
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