agentmods.dev

autoresearch

autoresearch is a skill for Claude Code, Codex from mrzhangguoguo/oh-my-workbuddy. It costs 50 tokens per session (863 once invoked), scanned A, original, MIT.

A persistent research loop that continues working until an explicit validator confirms the result. It can use script-based checks or a prompt-based review by an architect and professor-style critic.

In plain words
What is it for?
Use it for bounded research projects that need repeated investigation and a passing script or expert review before they are considered complete.
Why use it?
It helps with research deliverables that must meet defined acceptance criteria instead of stopping after an initial answer. The loop keeps evidence and validation status as part of the work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

not rated 2repo 2mo ago A scan 50 tokens original MIT

Good fit Use it for bounded research projects that need repeated investigation and a passing script or expert review before they are considered complete.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mrzhangguoguo/oh-my-workbuddy/autoresearch
View source ↗ mrzhangguoguo/oh-my-workbuddy
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.

Any agent
npx skills add mrzhangguoguo/oh-my-workbuddy --skill autoresearch
Clone the repo
git clone --depth 1 https://github.com/mrzhangguoguo/oh-my-workbuddy

Made for: Claude Code, Codex.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/autoresearch/github.svg)](https://agentmods.dev/skills/mrzhangguoguo/oh-my-workbuddy/autoresearch)
Your own site
<a href="https://agentmods.dev/skills/mrzhangguoguo/oh-my-workbuddy/autoresearch"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/autoresearch/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

Your own site · 80×15
<a href="https://agentmods.dev/skills/mrzhangguoguo/oh-my-workbuddy/autoresearch"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/autoresearch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 863 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 original No closer match found 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 $0.00050 $0.00863
Opus 5 $0.00025 $0.00432
Sonnet 5 $0.00010 $0.00173
Haiku 4.5 $0.00005 $0.00086

Measured 11d ago against content hash c295d9426957, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

autoresearch 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 11d 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.

skills/autoresearch/SKILL.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ported from oh-my-codex autoresearch. OMX runtime conventions ($macro invocation, omx CLI, .omx/ state directory) are replaced with WorkBuddy idioms (Skill tool, Agent tool, task list, .workbuddy/memory).

Autoresearch

Autoresearch is a skill-first, stateful research loop. It keeps the useful measured-research loop, but runs as a native WorkBuddy workflow (task list + .omw/ artifacts) instead of a direct CLI or tmux launch surface.

Boundary with planning research

Use autoresearch when the research output itself is a bounded deliverable that must pass an explicit validator. Do not recommend it for ordinary pre-planning docs lookup or general best-practice checks; use the research skill for that. If autoresearch is intentionally run before architecture planning, its approved artifact should feed evidence into ralplan; it should not become a final architecture/component unless the user explicitly asks for ongoing research automation.

Use when

  • You want a persistent research loop.
  • The task should keep nudging until explicit validation evidence exists.
  • You want init-time choice between script validation and prompt+architect validation.

Do not use when

  • You want a generic research/docs lookup (use research).
  • You have not decided the validation regime yet.

Core contract

  1. Init chooses validation mode. Pick exactly one:
    • mission-validator-script
    • prompt-architect-artifact
  2. Persist mode state in .omw/autoresearch/<slug>/autoresearch-state.json including:
    • validation_mode
    • completion_artifact_path
    • mission_validator_command or validator_prompt
    • optional output_artifact_path
  3. Completion is artifact-gated. The loop does not stop because the model says "done", because a hook fired once, or because several turns were no-ops.
  4. Intake + execution use skills: invoke the deep-interview skill (skill: deep-interview) with an autoresearch intake to clarify the mission + evaluator, then run the loop.

Read the full file on GitHub · 81 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. 11d ago First seen · 81 lines · 50 tokens per session scan A c295d9426957

Subscribe to this mod's changes

autoresearch is a skill published in the GitHub repository mrzhangguoguo/oh-my-workbuddy (2 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 863 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Researchagent-skillsoh-my-codexskillsworkbuddy
Related

Other skills, from other repositories

claude-md-improver

Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…

anthropics/claude-plugins-official · 82 tokens

agent-platform-rag-engine-management

Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…

google/skills · 85 tokens

gke-reliability

Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).

google/skills · 73 tokens

gke-workload-security

Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (auditcluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny…

google/skills · 181 tokens

agent-platform-model-registry

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

google/skills · 60 tokens

google-cloud-solution-agentic-analytics-spark-knowledge-catalog

Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…

google/skills · 138 tokens