Aegis is a method pack that guides coding agents to inspect a project's baseline, make bounded changes, and verify their work with fresh evidence. It is for people using coding-agent hosts who want fewer unverified changes and less unnecessary process. The catalogue add-ons implement this method through skills, instructions, commands, a hook, and a plugin.
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.
npx agentmods add skills/ganyuanran/aegis/executing-plansnpx skills add GanyuanRan/Aegis --skill executing-plansgit clone --depth 1 https://github.com/GanyuanRan/AegisWrote 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.
[](https://agentmods.dev/skills/ganyuanran/aegis/executing-plans)<a href="https://agentmods.dev/skills/ganyuanran/aegis/executing-plans"><img src="https://agentmods.dev/badge/skills/ganyuanran/aegis/executing-plans.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00041 | $0.02000 |
| Opus 5 | $0.00020 | $0.01000 |
| Sonnet 5 | $0.00008 | $0.00400 |
| Haiku 4.5 | $0.00004 | $0.00200 |
Grade A, and why
executing-plans 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Executing Plans
Overview
Load plan, review critically, execute all tasks, report when complete.
Announce at start: "I'm using the executing-plans skill to implement this plan."
For non-trivial execution, include Aegis Visibility: briefly tie the active
slice to its plan, checkpoint, drift or verification boundary. At completion,
pass plan adherence, evidence, complexity and residual risk to
verification-before-completion for the unified receipt.
If subagents are available and the plan has genuinely independent tasks,
prefer subagent-driven-development; lack of subagent support does not block
inline execution. Same-task agents share one workspace, and the coordinator
remains the only Git mutation owner.
The Process
Step 1: Load and Review Plan
- Read plan file
- If the plan or active checkpoint includes an
Execution Readiness View, read it before implementation and compare the plan against its intent lock, scope fence, baseline lock, owner / contract constraints, compatibility boundary, retirement boundary, test obligations, review gates, drift / rewind rules, and evidence required before completion. - Review critically - identify any questions or concerns about the plan
- If the view contradicts the plan, baseline, or current worktree evidence, return to plan review or refresh the advisory handoff before editing.
- Run the TDD Route Guard before implementation: confirm
Mode,Decision,Strict authority, strict signals, light eligibility,Test posture, and verification. Strict steps require either an explicit user/project request or a recorded auto decision; plan approval or risk labels alone are not authority. An off-mode missing record may be repaired only asMode: off / Decision: skippedwithout loading TDD. Missing/unsupported auto decisions return to plan review. An auto-light record is unsupported when any strict signal is present or when its tiny/low-risk/single-owner/no-behavior-change proof is incomplete. OnlyDecision: strictwith recorded strict authority may authorize steps namedWrite failing test,Verify RED,GREEN, orREFACTOR. Do not inferstrictduring execution. - If concerns: Raise them with your human partner before starting
- Before the first write, capture
TaskStartSnapshot: root,HEAD, branch or detached state, upstream divergence, staged/unstaged/untracked paths, active Git operations, andgit worktree list --porcelain. Preserve task-preexisting state; do not stash, reset, clean, or commit it. - Reuse the current branch unless rules require independent history or another goal owns it. If justified, switch/create it in the current workspace when safe; a worktree still requires concurrent checkout or blocking dirty state.
- If no concerns: Create TodoWrite and proceed
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.
- 5d ago First seen · 196 lines · 41 tokens per session scan A 25682af558d6
executing-plans is a skill published in the GitHub repository GanyuanRan/Aegis (1,167 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 2,000 once invoked, about $0.0002 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 2026-08-30.
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