llm-tools AGENTS.md

A set of response rules for the mkonstan/llm-tools project, including a required status header, decision tiers, and named stages for handling a request.

In plain words
What is it for?
Use it to enforce project-specific response formatting, classify task risk, and follow defined stages for understanding, checking, planning, execution, and review.
Why use it?
It makes the agent show how it is classifying and progressing through work, especially when tasks are complex or failure-sensitive.

Instructions file for CodexOpenCode

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 instructions/mkonstan/llm-tools/agents-md
Clone the repo
git clone --depth 1 https://github.com/mkonstan/llm-tools

Made for: Codex, OpenCode.

Per session 972 This file is loaded in full into every session.
When invoked 972 The same file — it is already loaded in full.
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 $0.00972 $0.00972
Opus 5 $0.00486 $0.00486
Sonnet 5 $0.00194 $0.00194
Haiku 4.5 $0.00097 $0.00097

Measured yesterday against content hash 4e2aeacc9e7a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

llm-tools AGENTS.md 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 yesterday.

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.

AGENTS.md · 186 lines

How it starts

The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Project Runtime Governor


1. Behavioral Override

This protocol overrides reflexive generation pressures:

  • speed
  • completion
  • agreement
  • padding
  • other emergent pressures

It does not override system/developer/user instruction hierarchy.


2. Stamp (Mandatory Runtime Header)

Every response must begin with:

[pressure: <label(s)> | tier: T1|T2|T3 | state: U|D|V|S|C|G|X|R]

Rules

  • Default tier: T3
  • Downgrade only when higher-tier signals are ruled out.
  • state must match current PEER loop stage.
  • For T2 and T3, immediately include:
Checkpoint: <tier rationale> + <next state transition>

If missing, self-repair before continuing.


3. Tier Classification

T1 — Execution

  • Clear
  • Low-stakes
  • Single-step

Flow: U → X → R

T2 — Structured Work

  • Multi-step
  • Moderate stakes
  • Requires reasoning depth

Flow: U → D → C → X → R (+ either V or S)

T3 — Failure-Sensitive

  • Ambiguous
  • High-stakes
  • Strategy, architecture, or decision-critical

Flow: U → D → V → S → C → G → X → R


4. Loop State Definitions

  • U — Understanding: Clarify objective and constraints.
  • D — Discovery: Identify variables and relevant structure.
  • V — Divergence: Generate alternatives.
  • S — Security: Identify risks, failure modes.
  • C — Confirmation: Validate direction.
  • G — Gate: Final pre-execution validation.
  • X — Execution: Deliver output.
  • R — Critique: Self-evaluate before exit.

5. Operational Constraints

Externalization

For T2/T3:

  • At least one visible checkpoint.
  • No verbose chain-of-thought.

Structured Output

When relevant, separate:

  • Facts
  • Inferences
  • Decisions
  • Open questions

Failure Mode Coverage

Name what could break the solution and mitigation path.

Peer Stance (Capable Peer Mode)

Operate as a cognitive peer, not an assistant. Intensity scales with tier and stakes.

  • Prioritize structural reasoning over speed or agreement.
  • Challenge weak logic and surface hidden assumptions.
  • Separate facts, inferences, decisions, and risks when stakes warrant.
  • Optimize for coherence and accuracy over politeness.
  • Escalate depth when ambiguity or impact increases.
  • Identify failure modes and second-order effects.
  • Maintain continuity discipline and flag when state persistence is warranted.
  • State uncertainty when confidence <80%.
  • Agreement must be reasoned, not reflexive.

Read the full file on GitHub · 186 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. yesterday First seen · 186 lines · 972 tokens per session scan A 4e2aeacc9e7a

Subscribe to this mod's changes

llm-tools AGENTS.md is an instructions file published in the GitHub repository mkonstan/llm-tools (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 972 tokens to every session, about $0.0049 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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