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autoresearch_evals

autoresearch_evals is a command for Claude Code, OpenCode from WdBlink/autoresearch-paper. It costs 18 tokens per session (1,288 once invoked), scanned A, a copy of autoresearch:evals, MIT.

A results analyser for tab-separated value (TSV) files produced by repeated iterations, such as experiment runs.

In plain words
What is it for?
Use it to find and analyse results files, infer whether higher or lower metrics are better when needed, and produce text, JSON, or Markdown output.
Why use it?
It makes trends, flat periods, declining gains, and regressions easier to see instead of requiring manual inspection of raw rows.

Command for Claude CodeOpenCode

Written for Claude Code and OpenCode: disable-model-invocation in frontmatter, but also installed under .opencode/.

not rated 2repo 4d ago A scan 18 tokens copy · 95% MIT

Good fit Use it to find and analyse results files, infer whether higher or lower metrics are better when needed, and produce text, JSON, or Markdown output.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/wdblink/autoresearch-paper/autoresearch_evals
View source ↗ WdBlink/autoresearch-paper
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/WdBlink/autoresearch-paper

Made for: Claude Code, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for autoresearch_evals

README.md
[![agentmods](https://agentmods.dev/badge/commands/wdblink/autoresearch-paper/autoresearch_evals/github.svg)](https://agentmods.dev/commands/wdblink/autoresearch-paper/autoresearch_evals)
Your own site
<a href="https://agentmods.dev/commands/wdblink/autoresearch-paper/autoresearch_evals"><img src="https://agentmods.dev/badge/commands/wdblink/autoresearch-paper/autoresearch_evals/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for autoresearch_evals

Your own site · 80×15
<a href="https://agentmods.dev/commands/wdblink/autoresearch-paper/autoresearch_evals"><img src="https://agentmods.dev/badge/commands/wdblink/autoresearch-paper/autoresearch_evals.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,288 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 95% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.01288
Opus 5.5 $0.00007 $0.00515
Sonnet 5.5 $0.00004 $0.00258
Haiku 4.5 $0.00002 $0.00129

Measured 3d ago against content hash 101ee2c40343, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

autoresearch_evals scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

95% identical to autoresearch:evals — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.opencode/commands/autoresearch_evals.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

EXECUTE IMMEDIATELY.

Parse Arguments

Extract from $ARGUMENTS:

  • Positional path to a specific TSV file
  • --format — output format: text (default console), json, md (markdown file)
  • --compare <path> — (v2.2.0 placeholder, not yet implemented)

Input Discovery

  1. If path provided → use that TSV directly
  2. If no path → scan current directory + autoresearch/*/ for *-results.tsv files
  3. If multiple found → question: "Which results to analyze?" — list found files
  4. If none found → question: "Provide path to results TSV"
  5. Also scan project root for v2.0.03 legacy TSV files (backward compat)

Parse TSV

  1. Read line 1: extract # metric_direction: higher_is_better|lower_is_better comment
    • If missing → infer from column names (metric/error_count → guess, or ask user)
  2. Read line 2: header row → detect available columns
  3. Read remaining lines: data rows
  4. Handle missing timestamp column gracefully (v2.0.03 compat)

Column Detection & Analysis

Activate analysis based on columns present in header:

Column Analysis
metric Trend direction, plateau detection (3+ flat iterations), diminishing returns, biggest single-iteration jumps
delta Per-iteration efficiency, cumulative improvement, effort-to-gain ratio
status Keep/discard rate, crash frequency, success streaks, failure clusters, longest winning streak
guard + guard-metric Guard failure rate, metric-improved-but-guard-failed analysis
severity Severity distribution (critical/high/medium/low/info), critical discovery rate per iteration
hypothesis + status Confirmation rate, investigation efficiency, most productive techniques
commit File hotspot analysis (cross-ref with git diff for kept commits), change size correlation
technique Technique effectiveness ranking
dimension Dimension coverage completeness (X/12)
candidate_label + judge_verdict Convergence speed, oscillation count
error_type Error category distribution, fix rate per category
classification New vs extension vs duplicate ratio, saturation curve
convergence_count Convergence trajectory

Read the full file on GitHub · 120 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 120 lines · 18 tokens per session scan A 101ee2c40343

Subscribe to this mod's changes

autoresearch_evals is a command published in the GitHub repository WdBlink/autoresearch-paper (2 stars, last pushed 4d ago), licensed MIT. It adds 18 tokens to every session and 1,288 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to autoresearch:evals, differing in 6 lines, and is treated as a copy.

Analytics and metricsacademic-writingagent-skillsaiai-agentsautonomous-research
Related

autoresearch_evals compared with commands from other repositories

autoresearch_evals next to 6 commands from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
autoresearch_evalsWdBlink/autoresearch-paperCommand24d agoMITA18Claude Code, OpenCode
ars-planImbad0202/academic-research-skillsCommand56kyesterdaynoneA19Claude Code
ars-revision-coachImbad0202/academic-research-skills-codexCommand14k5d agononeA27Claude Code
ars-3wImbad0202/academic-research-skills-codexCommand14k5d agononeA24Claude Code
nextProjectDXAI/labratCommand2373mo agoMITA0Claude Code
ja-fallbackZaious/journal-atlasCommand210d agononeA37Claude Code
ai-reviewStill-chowline394/MagicTeX-mcpCommand01mo agoAGPL-3.0A13Claude Code