Show HN: Ordewell – turn one goal into an ordered plan of coding-agent tasks
Turn one goal into an ordered plan of coding-agent tasks — each with its own runner, model and mode — then execute and verify it. Website · Docs What this is A plan you can rewrite before a token is spent. The plan is a typed artifact, not an agent's internal state: every task carries a runner, model, thinking effort and mode, and you can change any of them, add and remove tasks, and rewire dependencies — without losing completed work or round-tripping the AI.
- ▪Turn one goal into an ordered plan of coding-agent tasks — each with its own runner, model and mode — then execute and verify it.
- ▪Website · Docs What this is A plan you can rewrite before a token is spent.
- ▪The plan is a typed artifact, not an agent's internal state: every task carries a runner, model, thinking effort and mode, and you can change any of them, add and remove tasks, and rewire dependencies — without losing completed work or roun
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Story provenance
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Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/ordewell/ordewell |
| Publication time | Tue, 15 Sep 2026 13:31:37 +0000 |
| Retrieval time | 2026-09-15T14:16:52.483Z |
| Last seen | 2026-09-15T14:16:52.483Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | MoT_Gq3A7M9C · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Turn one goal into an ordered plan of coding-agent tasks — each with its own runner, model and mode — then execute and verify it. Website · Docs What this is A plan you can rewrite before a token is spent. The plan is a typed artifact, not an agent's internal state: every task carries a runner, model, thinking effort and mode, and you can change any of them, add and remove tasks, and rewire dependencies — without losing completed work or round-tripping the AI. The right model per task, chosen in the open. The planner makes one portfolio decision across the whole plan — a security refactor and a README update do not deserve the same model — and shows you every assignment before anything runs (why a separate planner?). Verdicts from evidence, not opinion.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.