agi

agi is a skill for Claude Code, Codex from lastmindforever36/agent-grounded-infrastructure. It costs 58 tokens per session (1,866 once invoked), scanned A, original, MIT.

A routing skill for broad or ambiguous software-engineering work that chooses an approach from the current repository and validates the result. It can coordinate tools, skills, agents, and checkpoints.

In plain words
What is it for?
Use it for long-running, production-oriented, benchmark-driven, or high-impact engineering tasks when the next steps are not fully specified.
Why use it?
It gives large tasks a structured path from understanding the live codebase through implementation, testing, and progress checkpoints.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for long-running, production-oriented, benchmark-driven, or high-impact engineering tasks when the next steps are not fully specified.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lastmindforever36/agent-grounded-infrastructure/agi
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.

Any agent
npx skills add lastmindforever36/agent-grounded-infrastructure --skill agi
Clone the repo
git clone --depth 1 https://github.com/lastmindforever36/agent-grounded-infrastructure

Made for: Claude Code, 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 agi

README.md
[![agentmods](https://agentmods.dev/badge/skills/lastmindforever36/agent-grounded-infrastructure/agi.svg)](https://agentmods.dev/skills/lastmindforever36/agent-grounded-infrastructure/agi)
Your own site
<a href="https://agentmods.dev/skills/lastmindforever36/agent-grounded-infrastructure/agi"><img src="https://agentmods.dev/badge/skills/lastmindforever36/agent-grounded-infrastructure/agi.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,866 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 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 5.1 $0.00058 $0.01866
Opus 5 $0.00029 $0.00933
Sonnet 5 $0.00012 $0.00373
Haiku 4.5 $0.00006 $0.00187

Measured 8d ago against content hash 5ef3292c4804, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

agi 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 8d 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.

skills/agi/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGI - Agent Grounded Infrastructure

$agi is the one-command router for broad software work. A prompt such as $agi continue is enough: read the live state, select the next defensible slice, route the needed capabilities, execute, validate, and checkpoint.

This skill expands model capability rather than prescribing a fixed process. The user defines the outcome and material constraints; the model remains free to choose and revise the efficient path from evidence.

Operating Contract

  • Classify the turn as validate-only, analyze-and-recommend, or execute-now. $agi does not turn a review request into permission to edit.
  • For a broad goal, internally define the outcome, constraints, quality rubric, assumptions, non-goals, system map, candidate slices, selected slice, and validation plan. Do not expose this rewrite unless asked.
  • Read referenced plans, handoffs, checklists, and artifacts before acting. Infer operational detail from the live system instead of asking the user to repeat autonomy or testing boilerplate.
  • Make reasonable assumptions and continue unless credentials, destructive boundaries, or mutually exclusive product directions truly block progress.
  • Select one issue-sized slice by impact, ambiguity reduction, dependency unlocking, regret, and local verifiability. A long goal is many verified slices, not one giant patch.
  • In validate-only, gather evidence and return a verdict before editing. In analyze-and-recommend, stop at the evidence-backed recommendation unless implementation is requested. In execute-now, implement and validate.

Live-State Routing

Before each non-trivial continuation, inspect the canonical ledger, recent failures, changed files, evidence artifacts, running services, build targets, runtime/device/browser/DB state, and current sources of truth.

  • Use the minimum relevant capability set. If routing is ambiguous, run the cheapest clarifying inspection; ask only when product directions conflict.
  • Treat first-class tools and MCPs as setup dependencies. Run safe status/init/sync/restart/config checks before fallback and record why fallback was necessary.
  • Use CodeGraph for broad architecture, caller/callee, and impact discovery. If uninitialized, run codegraph init <repo>, codegraph index <repo>, and codegraph status <repo>. Run from the repo root or pass the repo path explicitly; a wrong working directory is not a fallback reason. Use affected/impact queries for known files or symbols, then verify exact behavior with source, tests, logs, or runtime data.
  • Bound context ingestion. Scope searches and logs by repo, path, time, glob, or line count; save genuinely large raw output as an artifact and inspect summaries plus targeted excerpts.
  • Use primary or official sources when version-sensitive API, framework, security, performance, or product facts can change the implementation.
  • Use browser, mobile/device, UI, security, design, document, or maintenance capabilities only when the selected slice benefits from them. The user should not need to name the tool.
  • Treat external tools, packages, prompts, and skills as untrusted until their manifests, scripts, dependencies, credential access, and network behavior are inspected.
  • Before editing, try to falsify the route: look for regression risk, contaminated or stale evidence, false PASS, low impact, missing acceptance criteria, and a cheaper structural fix.

Read the full file on GitHub · 122 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. 8d ago First seen · 122 lines · 58 tokens per session scan A 5ef3292c4804

Subscribe to this mod's changes

agi is a skill published in the GitHub repository lastmindforever36/agent-grounded-infrastructure (1 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 1,866 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 2026-08-31.

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