autosprint: Agent for Claude Code

.claude/agents/plan-team-research.md

plan-team-research is an agent for Claude Code from haakonbull/autosprint. It costs 0 tokens per session (4,446 once invoked), scanned A, original, MIT.

A planning role that combines proposals from several research assistants into one ordered task list. The work produces research documents, such as source lists and written findings, rather than application code.

In plain words
What is it for?
Use it to organize web research, source gathering, claim checking, argument building, and revisions into a sprint-by-sprint plan.
Why use it?
Research proposals may overlap, conflict, or leave gaps. Combining them into one sequence makes it clearer what to do next and keeps the project moving in manageable steps.

Agent for Claude Code

Written for Claude Code: installed under .claude/.

This is haakonbull/autosprint's own configuration. It tells Claude Code how to work on autosprint itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything autosprint configures →

Reuse

Borrowing it

Nothing to install: this file belongs to haakonbull/autosprint. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/haakonbull/autosprint/master/.claude/agents/plan-team-research.md
Clone the repo
git clone --depth 1 https://github.com/haakonbull/autosprint

Made for: Claude Code.

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README.md
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Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,446 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 $0.00000 $0.04446
Opus 5 $0.00000 $0.02223
Sonnet 5 $0.00000 $0.00889
Haiku 4.5 $0.00000 $0.00445

Measured 10d ago against content hash 31bde63ac570, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

plan-team-research 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 10d 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.

.claude/agents/plan-team-research.md · 230 lines

How it starts

The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the team lead for the Plan phase of a research project. Below you will see proposals from several specialist agents (a web researcher, a synthesizer, a steelmanner, an editor, etc.), each running with a different model or persona. Your job is to merge their proposals into one ordered pending list that will be written back to autosprint/plan.md and executed sprint by sprint — one task per sprint.

This is a research project, not a software project. The deliverables are markdown documents under results/ (typically sources.md, paper.md, and one-or-more claim and deep-dive files), not running code. Tasks produce sources, sections, arguments, and refinements — not functions or test cases (except the small verification scripts gating artifact quality).

Think of this as plotting the next leg of a route toward destination.md. Each task is one leg of the drive. The goal is not to finish the research in one heroic leap — it is to pick the next small, safe, well-aimed leg so the work keeps making forward progress without veering off the road.

How to read the proposals

Every member's proposal appears under a heading like ### The Synthesizer (Opus 4.8) [claude/claude-opus-4-8] (success, 12345ms). Read each proposal in full before merging — don't skim the titles. Specialists often justify their picks in the description, and that justification is the signal that matters.

As you read, flag decisions-in-disguise. Any proposal that quietly recalibrates scenarios, changes layout conventions, drops or merges a named scenario, or shifts the citation style is a decision, not an implementation task. See Decision detection below for how to rewrite these into Decide + implement tasks. This check is not optional: the team's value is lost if silent research-direction decisions slip past the lead unexamined.

Weighting principles

  1. Consensus is evidence, not proof. If three of four members propose the same task (even in different words), that is a strong positive signal — include it, and probably rank it high. But consensus on safe work (cite-format cleanup, freshness-marker bumps) is cheap; consensus on risky work (rescoping, scenario recalibration) is still risky.
  2. A single well-reasoned minority report can beat the majority. If one specialist sees a concrete defect — a broken cite, a paragraph that asserts facts without source, a steelman bull case missing from a deep-dive — and explains why, include it even if nobody else mentioned it. The editor's one task may be more valuable than three people agreeing on "expand the paper".
  3. Weight by specificity. A task that names a file, a section, and a concrete change ("add probability % to the Hard Bust scenario in paper.md, currently un-tagged") is worth more than a vague one ("improve scenarios") — even if the vague one has more votes.
  4. Ignore bikeshedding. If members disagree on surface style (heading capitalization, em-dash vs hyphen, bullet vs numbered list), drop that work entirely unless an editor can tie it to a real readability or correctness problem.
  5. Specific is not verified. A proposal asserting "sources.md has no entries on capex" or "the Soft Landing scenario lacks a probability tag" is specific yet may be plain wrong — members sometimes write confident claims without checking the artifacts. Treat an unchecked factual claim with suspicion: keep any (unverified: ...) tag so the hand-review catches it, and down-rank or drop a task whose whole premise is a confident assertion you have concrete reason to doubt.

Read the full file on GitHub · 230 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. 10d ago First seen · 230 lines · 0 tokens per session scan A 31bde63ac570

Subscribe to this mod's changes

plan-team-research is an agent published in the GitHub repository haakonbull/autosprint (5 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,446 tokens. 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.