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.
npx skills add SNIKO/agent-skills --skill swe-researchgit clone --depth 1 https://github.com/SNIKO/agent-skillsWrote 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.
[](https://agentmods.dev/skills/sniko/agent-skills/swe-research)<a href="https://agentmods.dev/skills/sniko/agent-skills/swe-research"><img src="https://agentmods.dev/badge/skills/sniko/agent-skills/swe-research/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.
<a href="https://agentmods.dev/skills/sniko/agent-skills/swe-research"><img src="https://agentmods.dev/badge/skills/sniko/agent-skills/swe-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00051 | $0.01929 |
| Opus 5 | $0.00026 | $0.00964 |
| Sonnet 5 | $0.00010 | $0.00386 |
| Haiku 4.5 | $0.00005 | $0.00193 |
Grade A, and why
swe-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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline
swe-shape → swe-spec → [swe-plan] → [swe-worktree] → swe-execute → swe-review. This skill is not one of those stages: it runs at any point, standalone or delegated by any of them, often several times between two stages.
- This stage: answer one concrete factual question and preserve the evidence.
- Reads: the repository, external sources, the existing corpus, and any artifact the caller supplies.
- Writes: a subject report in the shared corpus, plus artifacts.
- Next: return the answer to whoever asked. The caller decides what to do with it.
Purpose
Answer a concrete engineering question with evidence, and add that evidence to a shared, long-lived research corpus so later changes reuse it instead of rediscovering it.
Research returns evidence to the caller; it does not change product intent, design, or contracts.
Invoke when the answer is worth preserving. Ordinary reading — "what does this function do", "where is this defined" — is not research and needs no artifact. Research is for questions whose answer another change, or another agent, would otherwise have to rediscover: how an external API actually behaves, what the blast radius of a change is, whether a dependency supports something, why a subsystem works the way it does.
Corpus
One shared corpus per repository, organized by subject, not by question:
.swe/research/
INDEX.md # generated — never edit by hand
<subject-slug>/
report.md
artifacts/
There is no per-change research directory. Findings about an API, a subsystem, or a dependency outlive the change that prompted them, and changes in the same repository overwhelmingly ask about the same domain and the same external services. A change references the reports it relied on from its own brief.md and spec.html.
A subject is a thing you can keep learning about: sec-edgar-api, tenant-resolution-middleware, legacy-dto-usage, postgres-jsonb-indexing. It is not a single question. report.md holds a standing summary plus dated findings; artifacts/ holds only what is needed to inspect or reproduce the evidence — probe scripts, captured responses, fixtures, benchmark output, query results. Omit artifacts/ when repository paths and cited sources fully support the answer.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 128 lines · 51 tokens per session scan A aac582cd9861
swe-research is a skill published in the GitHub repository SNIKO/agent-skills (2 stars, last pushed 16d ago), licensed MIT. It adds 51 tokens to every session and 1,929 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.
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