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/alexsds/ade-workflow/ade-generationnpx skills add alexsds/ade-workflow --skill ade-generationgit clone --depth 1 https://github.com/alexsds/ade-workflowWrote 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/alexsds/ade-workflow/ade-generation)<a href="https://agentmods.dev/skills/alexsds/ade-workflow/ade-generation"><img src="https://agentmods.dev/badge/skills/alexsds/ade-workflow/ade-generation.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 | $0.00078 | $0.01081 |
| Opus 5 | $0.00039 | $0.00541 |
| Sonnet 5 | $0.00016 | $0.00216 |
| Haiku 4.5 | $0.00008 | $0.00108 |
Grade A, and why
ade-generation 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 3d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADE Generation
Overview
The Generator is the builder in the ADE workflow. It implements features from an approved product plan one at a time, committing each to git, and hands off to the Evaluator for scoring.
Anthropic's research found two things about generators:
- They tend to "go off the rails" and stub features when working alone — the Evaluator catches this
- Even with Opus 4.6, the Generator still needs the Evaluator for "last mile" completeness
Self-evaluation before handoff is important but insufficient. The Generator checks that things work, but does not judge quality — that separation is the core of the harness design.
Build Workflow (4 Subphases from Anthropic Research)
1. Understand
Read the active plan from .ade/docs/plans/. Identify the current feature to implement. Understand:
- What this feature delivers to the user (from user stories)
- How it relates to features already built
- What the Evaluator will test against (user stories are the contract)
2. Implement
Build the feature. Figure out the technical approach yourself — the plan gives deliverables, not implementation details. This is by design: Anthropic found that micro-specified technical plans create more problems than they solve because incorrect assumptions cascade through every level.
- Implement what the plan describes, not more, not less
- Do NOT stub or skip features — if something is hard, build it fully or message the Evaluator explaining what blocks you
- Do NOT add features not in the plan — scope creep wastes evaluator cycles
- Build complete, working functionality — the Evaluator will test it as a real user would
3. Self-Verify
Quick sanity check before handoff:
- Does the app run without errors?
- Does the feature work at a basic level?
- Can you interact with it as a user would?
This is NOT a quality evaluation — that's the Evaluator's job. Self-verify catches obvious breakage so the Evaluator's time isn't wasted on features that don't even load.
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.
- 3d ago First seen · 111 lines · 78 tokens per session scan A c6caf9de16a3
ade-generation is a skill published in the GitHub repository alexsds/ade-workflow (1 stars, last pushed 5mo ago), licensed MIT. It adds 78 tokens to every session and 1,081 once invoked, about $0.0004 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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