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Ranked or semantic retrieval over durable records is deliberately not implemented

There is no vector store, no embedding, no relevance score and no index. search is a literal grep across the record kinds in a fixed order. This is a decision, published so that a reader can see it was refused rather than forgotten.

declared statusdeclared status: rejected Considered and deliberately refused, with the reason recorded.

recorded evidencerecorded evidence: no test Not judged: only a guaranteed claim is held to a recorded run. how evidence is recorded

The corpus is a handful of Markdown files and one JSONL. An index or an embedding store would be a second source of truth that has to be kept in step with the first, and a scan is faster than that problem. Revisited only if a repository appears where the scan is measurably too slow.

What it means

There is no vector store, no embedding, no relevance score and no index. search is a literal grep across the record kinds in a fixed order. This is a decision, published so that a reader can see it was refused rather than forgotten.

How it works

It does not. lib/search.sh shells out to grep -nF -i per record kind and prints what it finds.

How to see it

majordomus search "callback"        # substring match, authority order, no score
majordomus search "call.ack"        # exit 12: literal, so a regex is not a pattern here

What it does not cover

Everything an embedding would give you: synonyms, paraphrase, ranking by relevance, and finding the record that discusses a subject without naming it. If your records are numerous enough that this hurts, the honest answer today is that Majordomus is the wrong tool for that corpus.

Why it exists as a refusal

Three reasons, in order of weight.

An index is a second source of truth about what exists, and it can disagree with the records. Everything else in Majordomus is derived on read precisely so that this cannot happen; a stale index that quietly omits a handover is the same class of bug as a stale projection, with none of the stamping that catches one.

An embedding adds a dependency, a model call and a similarity threshold. The tool makes no network call and invokes no model anywhere, and a retrieval feature is a poor reason to breach that.

The corpus does not justify it. A repository's continuity records are a handful of Markdown files and one JSONL; a scan over them is faster than the staleness problem an index introduces.

Revisited when a repository appears where the scan is measurably too slow — measured, not assumed.

Detail rendered from docs/claims/semantic-retrieval.md.

From the statement to the proof

  1. 1 · the public statement

    Ranked or semantic retrieval over durable records is deliberately not implemented

    Made on Knowledge, Watch.

  2. 2 · the canonical claim

    semantic-retrievaldeclared status: rejected in docs/CLAIMS.yaml

    Defined in read it on this site · docs/CONTINUITY.md

  3. 3 · the implementation

    Nothing implements it yet.

  4. 4 · the test and the scenarios

    No executable evidence linked: the claim names no test, and no use case executes it.

  5. 5 · the recorded runs

    recorded evidence: no test how evidence is recorded

Where this claim is used

The moments this answers

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