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Task benchmark ​

Official v8.85.0 benchmark snapshot

Benchmark ID: sigmap-v8.85-main  ·  Date: 2026-10-27 (with R language)

MetricValue
Hit@5 (retrieval corpus, 105 tasks / 18 repos)80.4%
Honest grep comparison (125 tasks / 19 repos)92.8% vs 39.2% single-shot grep — 2.37× lift
Graph-boosted hit@580.4%
Honest lift (vs grep agent)2.37×
Prompt reduction44.4% (2.84 → 1.58)
Task success proxy61.9%
Token reduction (21 repos)95.2%
GPT-4o overflow (without → with)14/21 → 0/21

Latest saved run: 2026-10-27 (v8.85.0) — includes R language support (ggplot2, dplyr, shiny)

The success/proxy definitions and the task corpus are described in benchmark methodology.

This page answers the question people care about most:

does SigMap help the developer finish the task with fewer retries?

Headline result ​

MetricWithout SigMapWith SigMap
Task success proxy10%61.9%
Prompts per task2.841.6
Prompt reduction—44.4%
Retrieval hit@513.6%80.4%
Token reduction—95.2%

Why the task benchmark exists ​

Retrieval is a prerequisite, but not the whole story. Developers feel the difference as:

  • fewer prompt retries
  • fewer "can you share more files?" loops
  • fewer answers grounded in the wrong module

The task benchmark models that outcome from the ranked file quality tiers:

  • rank 1 hit → likely one prompt
  • rank 2–5 hit → likely follow-up prompt
  • miss → likely multiple retries

Current saved score card ​

TierMeaningTasksShare
CorrectRight file was ranked first6561.9%
PartialRight file was present but not first1918.1%
WrongRight file never surfaced in top 52120.0%

Prompt model summary ​

MetricValue
Average prompts without SigMap2.84
Average prompts with SigMap1.6
Reduction44.4%
Honest hit@5 lift2.37x — 92.8% vs 39.2% on the honest corpus (125 tasks / 19 repos); per-repo random lifts remain in the report as data

What changed in the v5 story ​

The earlier SigMap story was mostly "smaller context." The v5 story is more useful:

  • use ask to build the focused context
  • use validate to make sure coverage is healthy
  • use judge to check whether the answer was actually grounded
  • use learning when the same files repeatedly help or hurt

That makes the benchmark more than a marketing claim. It maps onto the actual daily workflow.

Benchmark snapshot by repo ​

RepoPrompt reductionCorrect / Partial / Wrong
express43.8%7 / 1 / 0
flask34.8%5 / 0 / 3
gin61.8%7 / 1 / 0
spring-petclinic44.8%4 / 0 / 1
rails53.3%3 / 2 / 0
axios32.1%4 / 1 / 3
rust-analyzer59.9%4 / 1 / 0
abseil-cpp53.2%3 / 2 / 0
serilog4.7%0 / 1 / 4
riverpod53.1%4 / 0 / 1
okhttp55.0%4 / 1 / 0
laravel60.0%4 / 1 / 0
akka46.2%2 / 3 / 0
vapor5.2%0 / 1 / 4
vue-core59.6%4 / 1 / 0
svelte39.7%2 / 2 / 1
fastify37.7%5 / 0 / 3
fastapi44.4%3 / 1 / 1

These rows show why the task benchmark matters. Some repos have great retrieval lift but still need workflow help around validation and judge-based trust.

Reproduce ​

bash
node scripts/run-task-benchmark.mjs --save
node scripts/run-task-benchmark.mjs --json

For the full multi-benchmark dashboard:

bash
node scripts/run-benchmark-matrix.mjs --save --skip-clone
open benchmarks/reports/benchmark-report.html

MIT License