Research potential award nominees with explicit completeness checks

Why use this

1. An award researcher may collect many promising names but find that only some profiles contain enough evidence to assess the stated criteria. Search visibility can also skew the list toward certain regions, institutions or well-publicized achievements.

2. This job could make profile completeness and search coverage visible before reviewers discuss nominees. Separating discovery from eligibility and selection keeps an incomplete name list from looking like a finished, balanced assessment.

Why an agent / simpler alternative

Useful judgment

Map public professional evidence to explicit criteria and identify missing information or uneven search coverage.

Simpler alternative

Use a committee's existing candidate nominations when they already include complete supporting evidence.

Unsuitable when

The task infers protected traits, guesses eligibility or automatically selects winners from uneven public data.

Proposed inputs

1. Name

   Award criteria

   Owner

   Authorized research owner

   Minimum scope

   Official scope, eligibility rules and review requirements

   Quality check

   Identify what needs documentary confirmation

2. Name

   Candidate evidence

   Owner

   Researcher

   Minimum scope

   Permitted public achievements and professional biographies

   Quality check

   Track attribution, dates and unanswered fields

Access and setup — proposed or unknown

Proposed minimum

1. Begin with fictional profiles and a completeness matrix; no real-person profiling, nomination submission or contact.

Compatibility unknowns

1. Current public-source reachability, eligibility evidence and exact runtime compatibility are unknown.

External actions requiring approval

1. Contacting candidates, sharing sensitive information or submitting nominations requires specific authorization and human selection.

Expected deliverable and review checks

Proposed artifact

Candidate-research matrix with criterion evidence, missing fields, search-coverage notes and unresolved eligibility.

Critical checks

1. Distinguish names from complete profiles; do not infer age or identity traits; keep source gaps visible rather than silently excluding people.

Missing output evidence

This overlay adds no new output inspection, execution or validation; consult the referenced canonical source outcome limits.

Failure signals and proposed responses

1. Signal

   A well-publicized profile seems stronger because it is fuller

   Why it matters

   Documentation volume biases judgment

   Proposed response

   Separate evidence completeness from merit assessment.

2. Signal

   Missing eligibility facts are guessed from education dates

   Why it matters

   An unsupported inference becomes a screening decision

   Proposed response

   Mark eligibility unverified and request appropriate evidence.

Effort and cost — unknown

Setup work

1. Define completeness fields and permitted research boundaries.

Ongoing review

1. Human reviewers resolve eligibility and assess candidates under the official criteria.

Unknowns

1. Public-record quality, coverage bias, verification effort and research costs are unknown.

First check — proposed, unexecuted

Status

proposed_unexecuted

Synthetic fixture

Invent five professional profiles with uneven documentation and regional search coverage; prepare a completeness review without ranking merit.

Acceptance checks

1. Flag missing eligibility; distinguish coverage from quality; avoid sensitive inference; nominate nobody.

Stop conditions

1. Stop if eligibility depends on guessing or selection would rely on sensitive personal characteristics.

Limits

1. A discovery list cannot establish balanced coverage, verified eligibility or the deservingness of any nominee.