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Source 0067 — As a User, I want to find the most suitable Agent for my Task

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3 November 2026, 18:14
Comments12 peopleConnectionsAttributes13

Source decision 0067 — As a User, I want to find the most suitable Agent for my Task


    Original source · exact version bafyreia6tce3e3dm3rkglvtoi7huecf67674b6gj6vc7le53h2noc46wna

    Classification: story; source kind: story; decision: approve; confidence: low; review status: needs-review.

    Rationale: Classification follows the source’s stated user-facing intent and content; sparse or exploratory sources remain reviewable rather than being merged or embellished.

    Review qualification: Uncertain identity/behavior/duplication remains a separate candidate; do not merge without review.

    Canonical target (to be published after manifest): Proposed canonical target

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No text blocks in this source; title and source metadata retained.

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Attributes
name
Source 0067 — As a User, I want to find the most suitable Agent for my Task
owner
status
needs-review
sources
1.
localContextAs a User, I want to find the most suitable Agent for my Task
reviewStatusneeds-review
sourceVersionbafyreia6tce3e3dm3rkglvtoi7huecf67674b6gj6vc7le53h2noc46wna
sourceDocument
extractionRationaleClassification follows the source’s stated user-facing intent and content; sparse or exploratory sources remain reviewable rather than being merged or embellished.
reviewer
confidence
low
provenance
1.
localContextAs a User, I want to find the most suitable Agent for my Task
reviewStatusneeds-review
sourceVersionbafyreia6tce3e3dm3rkglvtoi7huecf67674b6gj6vc7le53h2noc46wna
sourceDocument
extractionRationaleClassification follows the source’s stated user-facing intent and content; sparse or exploratory sources remain reviewable rather than being merged or embellished.
candidateType
story
proposedRecord
reviewDecision
approve
reviewRationale
Horacio-authorized source-faithful migration decision. Near matches deliberately remain separate pending reviewer reconciliation.
duplicateCandidates

Empty list

classificationRationale
Classification follows the source’s stated user-facing intent and content; sparse or exploratory sources remain reviewable rather than being merged or embellished.
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