agentsclimarketplace

Retrieve

Skill opendatadiscovery/odd-team/.claude/skills/retrieve

Run the graph-retriever subagent — intelligent, iterative retrieval over the derived graph query layer. The maintainer asks a free-form information-need question ("where is X", "what depends on Y", "which findings concern Z"); the agent constructs a strong query, runs a bounded retrieve→read→judge→refine loop (≤10 iterations) with adaptive traversal, and returns a cited answer set. Emits substrate-refinement suggestions to lineage/{repo}/retrieval-feedback/ without ever mutating the graph. Supersedes the grep-based registry-search. Per adrs/drafts/agentic-graph-retriever.md.From its SKILL.md

Install
npx -y skills add opendatadiscovery/odd-team --skill retrieve

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.1 KB, 869 tokens by cl100k_base, as published. Nobody here has run it

/retrieve — intelligent iterative retrieval over the ontology graph

The query-time companion to the derived graph query layer. Where query (the CLI) does one static hybrid pass, /retrieve spawns the graph-retriever subagent — which iterates: it searches, reads the full content of what came back, reasons about the gap, reformulates the query to discriminate, traverses neighbours at a self-chosen depth, and converges on a cited answer. It exists because the static query() has a measured recall ceiling (it fails the maiden gold-set gate); an agentic loop does not commit to one formulation.

It is also a substrate-quality probe: when a retrieval surfaces a stale / thin / mis-described node, the agent records a structured refinement suggestion in lineage/{repo}/retrieval-feedback/ for a future /enrich or reducer batch to apply. It never mutates the graph — read-only, suggest-only.

Argument forms

FormBehaviour
/retrieve "<question>" [--repo <repo>]Default. Spawn graph-retriever on the question. Repo defaults to odd-platform.
/retrieve (no args)Ask the maintainer for the question via AskUserQuestion, then proceed.

Prerequisites

  • The graph query layer is installed: lineage/_extractor/.venv/ exists with the embeddings extra (uv sync --extra embeddings in lineage/_extractor). If not, the retriever still runs graph-only (keyword-seeded) — degraded but functional.
  • The substrate exists: lineage/{repo}/nodes.jsonl + understanding/ sidecars + the reducer detail/ dirs. The agent's first tool call builds the ephemeral graph (~8 s, one-time per substrate change; a build cache makes later calls sub-second).

Protocol

1. Capture the question

If the maintainer passed it as the first argument, use it verbatim. If not, AskUserQuestion:

"What do you want to retrieve? Free-form — the agent searches, reads, refines, and returns a cited answer set. Examples: 'every endpoint the alert API exposes', 'what reads the notifications config', 'which findings concern the lineage depth parameter'."

2. Resolve the repo

--repo flag, else default odd-platform.

3. Spawn the graph-retriever subagent

Spawn graph-retriever (.claude/agents/graph-retriever.md) with a prompt that gives it:

  • the maintainer's question, verbatim;
  • the repo;
  • the reminder that it has ≤10 iterations, must cite every answer node source_file:source_line, must stay read-only on the graph, and must write any substrate-refinement suggestions to lineage/{repo}/retrieval-feedback/{date}-{slug}.md.

The agent owns the loop — query construction, iteration, adaptive traversal depth, convergence, and the suggestion side-channel. Do not micro-manage it.

4. Relay

Relay the agent's answer to the maintainer: the cited answer node set, the confidence, and the iteration trace. If the agent wrote a retrieval-feedback/ file, surface its path — those suggestions are input for the next enrichment batch.

Notes

  • /retrieve supersedes the registry-search subagent for query/dedup needs. A reducer doing cross-batch dedup can spawn graph-retriever with a dedup-nearest-shaped question instead of grep-over-sharded-indexes.
  • The retrieval result is advisory. The maintainer applies judgment — the agent finds and cites; it does not decide.
  • Case-law / design: adrs/drafts/agentic-graph-retriever.md; tool layer: adrs/drafts/graph-query-layer.md.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,144. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.