Proposed specificationSource-located exemplarH2 H3

Multi-objective evolution and composition

Search among competing objectives.

JOIN POINTcandidate_harness_selectionRECORD STATUSCandidate · v0.1.0

UML class view

The proposed contract drawn as participant roles, received calls, and numbered dependencies.

Object interactions

The same roles and calls as a class collaboration and a numbered message sequence.

Object interaction diagram for Multi-objective evolution and composition, showing role collaboration and a numbered message sequence — FIG. E04 / OBJECT INTERACTIONS
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Pointcut

Where the mechanism applies. All four dimensions belong to the proposed match, not just its vocabulary.

Context: Candidate harnesses differ across at least two measured objectives.
Trigger: Evaluation yields an objective vector.
Structure: Declared objectives, constraints, candidate set, and Pareto or scalar selection.
Effect: Selected candidates preserve documented trade-offs rather than one hidden score.

Protected contract

The obligation that clients, operators, and auditors should be able to rely on.

Requires: Objective direction, weight, and constraints are explicit.
Ensures: Selection records candidate vectors and dominance or scoring rationale.
Invariant: A hard constraint failure cannot be hidden by strong average quality.
Violation: Missing objective or incomparable candidate is marked ineligible or ambiguous.

Negative control

A single accuracy score is not multi-objective selection.

Variation & lifecycle

The hot spot is admitted only where the protected semantics survive.

Permitted variation

Quality-cost trade-off, Pareto front, weighted fitness, and constraints.

Test obligation

Test dominance, ties, constraint failure, missing objective, and composition.

Evolution question

Did harness optimization expose more objectives and constraints?

Prompt + code design

An illustrative prompt and a small design sketch for the proposed contract. Names and APIs are invented; this is not a repository excerpt.

PROMPT SKETCH

State objective direction, weights, and constraints before evaluating candidates. Record the candidate vectors and the dominance or scoring rationale behind the selection.

CODE DESIGN / PYTHON

def select(candidates, objectives):
    scored = [objectives.score(candidate) for candidate in candidates]
    frontier = pareto_front(scored)
    chosen = objectives.tie_break(frontier)
    return Selection(
        chosen,
        vectors=[item.vector for item in scored],
        frontier=[item.id for item in frontier],
    )

Illustrative design sketch. A Pareto front explains trade-offs; a single unlabeled score hides them. This example is a teaching aid, not implementation evidence or a conformance claim.

Detection & matching

The frozen rule that retrieves this record, the canonical source exemplar, and the control that should stay unmatched.

Join point: candidate_harness_selection
Source locator: See the source record.
Lexical cue: (?i)\b(?:multi[_-]?objective|pareto|fitness[_-]?function|objective[_-]?weights?)\bFrozen expression, v0.1.0. A match is a retrieval cue, not a confirmed implementation.
Aliases: multiobjective, paretofront, objectiveweights, candidateselection
Canonical exemplar: mingju-c/HarnessForgeHarnessForge_4B/tools/half_select_harnesses.py:108Support: HarnessForge_4B/registries/README.md:48
Negative control: A single accuracy score is not multi-objective selection.

Scope-anchored review. pohe-agent analyze <repo> --pattern E04 anchors the cue to its enclosing declaration and checks a separate operational signature for all four pointcut dimensions. Missing roles and negative-control risks remain visible; a structural match is not E2/E3. Calibration report ↗

Repository files

Up to five public files retrieved by the frozen cue and pinned to the audited commit. A match is a place to inspect, not a confirmed implementation.

01mingju-c/HarnessForgeHarnessForge_4B/tools/half_select_harnesses.py:108CANONICAL SOURCE 02cline/clinesdk/packages/llms/src/catalog/catalog.generated.ts:11221RETRIEVAL CUE 03Darwin-Agent/HarnessXharnessx/meta_harness/agent.py:765RETRIEVAL CUE 04mastra-ai/mastradocs/src/content/en/models/sidebars.js:834RETRIEVAL CUE 05OpenHands/software-agent-sdkexamples/01_standalone_sdk/59_route_task_to_model.py:126RETRIEVAL CUE

Evidence & provenance

Each layer answers a different question. Do not substitute retrieval for review.

Source-located exemplar

A concrete source anchor is available for this proposed record. It is one exemplar, not evidence that all repositories—or every contract field—conform.

Review boundary: this candidate and its specification come from an AI-assisted study. Independent human validation remains open.

ANY-EVIDENCE FAMILY COVERAGE8/36

22.2% of repository families in the frozen panel have at least one current cue, historical cue, or canonical source layer. This is not confirmed prevalence.

Current lexical-cue repositories: 9 / 41

Canonical source anchormingju-c/HarnessForge 8bef9488c35aHarnessForge_4B/tools/half_select_harnesses.py:108

Supporting surfaceHarnessForge_4B/registries/README.md:48

Pareto-front harness selection over quality and cost objectives.

Exploratory retrieval cue Regex / v0.1.0

(?i)\b(?:multi[_-]?objective|pareto|fitness[_-]?function|objective[_-]?weights?)\b

This expression is a discovery instrument only. A match is a retrieval cue—not a confirmed implementation, pointcut match, or contract proof.