GOVCON AGENT BENCHMARK

Benchmark Methodology

The methodology defines task packets, source requirements, rubric scoring, reviewer expectations, and failure-mode tracking for GovCon AI agents.

Task packet design

Each task packet should mirror how GovCon work is assigned, performed, reviewed, and defended.

Packets can include solicitations, amendments, award records, budgets, past performance, internal templates, contract files, and evaluation criteria. Synthetic data is acceptable when public release of real data is not approved.

Rubric scoring

Rubrics cover source faithfulness, completeness, compliance awareness, govcon domain reasoning, output usability, auditability, human-review readiness, security posture awareness.

Reviewers should score the work product, not just the final answer. Strong outputs cite sources, preserve assumptions, expose uncertainty, and produce artifacts a human can review.

Publication rules

Do not publish competitor scores until the methodology, evaluation data, and legal review are ready.

Until then, benchmark pages should focus on the evaluation standard, sample task structure, and why these work products require a domain-specific approach.

FAQ

Questions teams ask before they switch

Who scores the tasks?

The target model is expert review by GovCon operators using written rubrics and documented failure modes.

Can the benchmark use real solicitations?

Yes when public and appropriate, but sensitive or customer-specific material should be replaced with synthetic or sanitized task packets.

What is the main scoring risk?

Overstating precision. The methodology should preserve uncertainty and make reviewer judgment explicit.

Working session

Bring a live pursuit. We will run the workflow in front of you.

GovSignals is easiest to evaluate against real work: a target agency, recompete, RFP package, compliance question, or competitor comparison.

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