engifoundry-exec

engifoundry-exec is a skill for Claude Code from caoyuan-fire/engi-foundry-skill. It costs 61 tokens per session (2,112 once invoked), scanned A, original, Apache-2.0.

An execution workflow for ready-made EngiFoundry engineering jobs. EngiFoundry is a structured system for planning, reviewing, checking, and handing over software work.

In plain words
What is it for?
Use it to carry out an already approved package of engineering work and record concise results for review or handoff.
Why use it?
It ensures jobs run in the required order and follow the project's configured rules, contracts, and availability checks.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the engifoundry-bundle plugin — 10 skills, 1 hook, 1 MCP server shipped together

Good fit Use it to carry out an already approved package of engineering work and record concise results for review or handoff.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/caoyuan-fire/engi-foundry-skill/engifoundry-exec
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 caoyuan-fire/engi-foundry-skill --skill engifoundry-exec
Clone the repo
git clone --depth 1 https://github.com/caoyuan-fire/engi-foundry-skill

Made for: Claude Code.

Or install engifoundry-bundle, the plugin that ships this one along with the rest of its 10 skills, 1 hook, 1 MCP server.

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 engifoundry-exec

README.md
[![agentmods](https://agentmods.dev/badge/skills/caoyuan-fire/engi-foundry-skill/engifoundry-exec/github.svg)](https://agentmods.dev/skills/caoyuan-fire/engi-foundry-skill/engifoundry-exec)
Your own site
<a href="https://agentmods.dev/skills/caoyuan-fire/engi-foundry-skill/engifoundry-exec"><img src="https://agentmods.dev/badge/skills/caoyuan-fire/engi-foundry-skill/engifoundry-exec/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 engifoundry-exec

Your own site · 80×15
<a href="https://agentmods.dev/skills/caoyuan-fire/engi-foundry-skill/engifoundry-exec"><img src="https://agentmods.dev/badge/skills/caoyuan-fire/engi-foundry-skill/engifoundry-exec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,112 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 $0.00061 $0.02112
Opus 5 $0.00030 $0.01056
Sonnet 5 $0.00012 $0.00422
Haiku 4.5 $0.00006 $0.00211

Measured 9d ago against content hash 928c0e47a904, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

engifoundry-exec 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 9d 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/engifoundry-exec/SKILL.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

EngiFoundry Exec

Execution Selection

This section applies only to the controlling Agent arranging execution. A session that received engifoundry.executor-task/v1 is already the Executor Worker; the protocol is a terminal routing fact. It skips Executor selection and invocation, must not compare or infer its model identity, executes only the referenced Job, and returns one engifoundry.executor-handback/v1 object. It must never invoke or select another Executor.

The controlling Agent reads ./engifoundry.config.json, the project-owned workspace guide, the complete Executor and Workflow config files, contracts.md, and executor-task.template.json in full. Follow the Executor config's schemaRef and read that complete schema before selecting or invoking an Executor. Do not extract only executor, command, model, or usage; the surrounding fields and every declared Gate remain binding. Then read the Phase, PAK, and Job contracts before acting.

Compare only the active model with the configured Executor model; CLI identity and executorId do not decide execution ownership. When the configuration pins the same canonical model as the active model, the controlling Agent directly executes eligible Jobs in the current session without invoking an Executor Worker or producing a Worker handback. This is normal configured execution, not fallback or self-approval. The controlling Agent still applies all Exec discipline, evidence, Review, approval, and completion rules.

When the pinned models differ, invoke the configured Executor through its verified CLI usage, including the configured canonical model argument. A cli-default selection makes no model identity promise and therefore has no same-model fast path; invoke its configured CLI. Once the invocation accepts the task, model selection is settled by the controlling session and the receiving Worker executes it. Natural-language model self-identification is not trusted evidence: a model may know only its family name rather than the configured product alias.

Read the full file on GitHub · 70 lines

Files

What ships with it

2 files 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. 9d ago First seen · 70 lines · 61 tokens per session scan A 928c0e47a904

Subscribe to this mod's changes

engifoundry-exec is a skill published in the GitHub repository caoyuan-fire/engi-foundry-skill (2 stars, last pushed 15d ago), licensed Apache-2.0. It adds 61 tokens to every session and 2,112 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.

Related

Other skills, from other repositories

julilaoshi-design

Public-safe julilaoshi-design workflow for official Pencil MCP execution and the free browser-first julilaoshi-design Web 2.0 editor. Use when a task needs Pencil handshake/canvas edits, .pen execution, screenshot review, or lightweight HTML design-to-web tweaking without redistributing official Pencil or leaking…

julilaoshi/julilaoshi-design · 68 tokens

x-insight-cards

Run scheduled or manual creator curation that turns recent high-quality X posts into verified image-and-caption packs for Douyin and Xiaohongshu review, with optional private delivery to a pinned WeChat iLink bot review chat or confirmed File Transfer Assistant self-chat. Use when Codex needs to discover, verify…

ljunnan24-hash/x-insight-cards · 121 tokens

zhuoyu-workshop

Student project delivery and packaging workflow for Codex. Use when the user needs help with Chinese university student projects, course projects, innovation training projects, competitions, capstones, graduation projects, project defense decks, closing reports, README/GitHub showcase materials, software copyright…

handsomeZR-netizen/zhuoyu-workshop-skill · 81 tokens

project-engineering-strategy

Use when a software project needs durable cross-session governance for formal documents, WBS or tracker coordination, worktree delivery boundaries, evidence and acceptance states, handoffs, or architecture and design-document control.

wgwtest/project-engineering-strategy · 46 tokens

codex-autoresearch

Run autonomous, measurable experiments in a Git repository: change one hypothesis, verify a numeric metric, keep improvements, and revert failures. Use when the user wants Codex to keep iterating toward a numeric target in the foreground or as a detached background run. Do not use for ordinary one-shot coding…

leo-lilinxiao/codex-autoresearch · 80 tokens

xiaohongshu-conversion-path

A Xiaohongshu conversion-path guide maps how people move from seeing content on Xiaohongshu, a Chinese social-content platform, to taking a next step such as messaging, booking, trying a tool, or buying.

mengke-wang/xiaohongshu-ai-workbench · 168 tokens