research

research is a command for coding agents from srstomp/pokayokay. It costs 6 tokens per session (543 once invoked), scanned A, original, MIT.

A process for researching a major technical or business decision across multiple sources and producing a written comparison. It covers technology evaluations, competitor analysis, architecture choices, and vendor selection.

In plain words
What is it for?
Use it to scope research, gather documentation and benchmarks, compare options, record findings, and create a report for stakeholders.
Why use it?
It turns a broad decision into defined questions, criteria, trade-offs, and a reasoned recommendation.

Command

Part of the pokayokay plugin — 17 skills, 23 commands, 14 agents, 4 hooks, 1 MCP server shipped together

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.

agentmods
npx agentmods add commands/srstomp/pokayokay/research
Clone the repo
git clone --depth 1 https://github.com/srstomp/pokayokay

Or install pokayokay, the plugin that ships this one along with the rest of its 17 skills, 23 commands, 14 agents, 4 hooks, 1 MCP server.

Per session 6 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 543 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00006 $0.00543
Opus 5 $0.00003 $0.00271
Sonnet 5 $0.00001 $0.00109
Haiku 4.5 $0.00001 $0.00054

Measured 3d ago against content hash 207559cbe3a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 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.

plugins/pokayokay/commands/research.md · 103 lines

How it starts

The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Research Workflow

Research: $ARGUMENTS

When to Use

Use /pokayokay:research for multi-day investigations:

  • Technology evaluation
  • Competitive analysis
  • Architecture exploration
  • Vendor selection

For quick (2-4 hour) investigations, use /pokayokay:spike instead.

Steps

1. Scope the Research

Define clearly:

  • Primary question: What decision does this inform?
  • Criteria: How will we evaluate options?
  • Constraints: Budget, timeline, team skills
  • Stakeholders: Who needs the output?

2. Create Research Task

npx @stevestomp/ohno-cli create "Research: $TOPIC" -t research

3. Gather Sources

  • Official documentation
  • Community resources (GitHub, Stack Overflow)
  • Case studies and benchmarks
  • Expert opinions and comparisons

4. Evaluate Options

Against defined criteria:

  • Technical fit
  • Learning curve
  • Community support
  • Long-term viability
  • Cost implications

5. Synthesize Findings

  • Compare options in structured format
  • Identify trade-offs
  • Form recommendation with rationale

6. Generate Report

Create .claude/research/[topic]-[date].md:

# Research: [Topic]

## Question
[The decision this informs]

## Options Evaluated
[List with brief description]

## Evaluation Matrix
| Criteria | Option A | Option B | Option C |
|----------|----------|----------|----------|

## Recommendation
[Primary recommendation with rationale]

## Trade-offs
[What you give up with this choice]

## Next Steps
[Follow-up actions]

7. Create Follow-up Tasks

npx @stevestomp/ohno-cli create "[implementation task]" -t feature

Covers

  • Technology evaluation
  • Vendor comparison
  • Architecture decisions
  • Build vs buy analysis
  • Migration planning
  • /pokayokay:spike - Shorter time-boxed investigation
  • /pokayokay:arch - Architecture review
  • /pokayokay:work - Implement chosen approach

Skill Integration

When research involves:

  • Architecture patterns → Also load architecture-review skill
  • Security evaluation → Also load security-audit skill
  • Database options → Also load database-design skill

Read the full file on GitHub · 103 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 · 103 lines · 6 tokens per session scan A 207559cbe3a1

Subscribe to this mod's changes

research is a command published in the GitHub repository srstomp/pokayokay (9 stars, last pushed 2mo ago), licensed MIT. It adds 6 tokens to every session and 543 once invoked, about $0.0000 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.