How AgentCodex Works
A transparent trust center for source collection, extraction, confidence, scoring, and published release intelligence.
Confidence
Extracted / EST
not all values are measured
Capability Scale
1-10
normalized dimensions
Metadata Gaps
Honest
not captured is shown plainly
What We Track
Version-aware release intelligence, not benchmark leaderboards
Scope
AgentCodex monitors agent releases, version notes, source links, and structured metadata. Each published record becomes part of the radar, profile timeline, directory, comparison, and copilot shortlist layers.
Pipeline
How a source becomes an AgentCodex signal
Source ingestion
Official changelogs, docs, blogs, and source URLs are collected as candidate release evidence.
Extraction
Release text is converted into structured fields like version, change summary, context, pricing, and capabilities.
Validation
Invalid values are sanitized and confidence/source signals are attached before publishing.
Scoring
Capability dimensions and movement deltas are normalized for comparison and radar views.
Publishing
Approved records power Radar, profiles, directory, compare, categories, and copilot shortlists.
Confidence, EST, and Missing Fields
Trust Model
Confidence comes from extraction confidence when present. If missing, AgentCodex shows an estimated confidence badge instead of pretending it is measured.
Context window and pricing are shown only when captured on a release or carried forward as a last-known metadata value.
Source trust indicates whether a release source matches known official domains for that agent.
FAQ
What mechanism are you using to rate the models?
AgentCodex scores each release version across standardized capability dimensions on a 1 to 10 scale. Scores are derived from release evidence and normalized through validation and calibration rules so missing or invalid values do not distort results.
What are you using under the hood during comparison?
Comparison is version-aware and capability-weighted. AgentCodex aligns each selected agent's latest published profile, applies preset workflow weights, and shows side-by-side capability fit with direct links back to source-aware version context.
Is this benchmark data or live product intelligence?
It is release intelligence, not a synthetic benchmark leaderboard. AgentCodex tracks shipped updates from public sources and highlights what changed, when it changed, and where the source signal came from.
How do you reduce bias or inconsistency?
We use fixed capability dimensions, deterministic validation rules, source-quality signals, and human review workflows for drafts. This keeps scoring more consistent and easier to audit over time.