Task reading
Implementation task
AgentQuote reads the task type, repo size, ambiguity, privacy risk, and review capacity before choosing a route.
Pre-run decision layer
Pick the right agent setup before the work begins.
AgentQuote helps engineering teams decide whether a task should go to Codex, Claude, an open model, a local workflow, or a staged agent route. It optimizes for outcome quality and developer flow, not just token spend.
Agent fit
Quality risk
Human review effort
Route advisor
Describe the task
Recommended setup
Codex direct implementation
Outcome fit
High
Token value
Good
Moderate usage, low coordination
Review effort
Low
Reliability
High
Alternatives
Route comparison
| Agent setup | Use when | Outcome fit | Token value | Review effort | Main tradeoff |
|---|
Decision signals
What the advisor considers
Operating note
Keep humans in the loop
For production code, AgentQuote treats the recommendation as a planning decision. Developers still review diffs, tests, sensitive context, and deployment impact.
Prototype to product
What would make this real.
Connect run history
Learn from actual task outcomes, model usage, retries, and review notes.
Read repo signals
Estimate context size, test coverage, language mix, and risky files.
Recommend routes
Choose a single agent or staged setup based on task requirements.
Close the loop
Update recommendations after each run succeeds, fails, or needs review.