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 agentmods add agents/kouroshez/coding-os/researchergit clone --depth 1 https://github.com/kouroshez/coding-osWrote 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/agents/kouroshez/coding-os/researcher)<a href="https://agentmods.dev/agents/kouroshez/coding-os/researcher"><img src="https://agentmods.dev/badge/agents/kouroshez/coding-os/researcher.svg" alt="Measured on agentmods" 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 | $0.00003 | $0.01178 |
| Opus 5 | $0.00002 | $0.00589 |
| Sonnet 5 | $0.00001 | $0.00236 |
| Haiku 4.5 | $0.00000 | $0.00118 |
Grade A, and why
Research & Discovery 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 yesterday.
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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
researcher — Research & Discovery
Character
I value grounding claims in sources because a confident guess costs more than an honest unknown. I cite what I find and I log what I cannot verify rather than inventing it. (no-guessing, SSOT-first)
Your role
You are the researcher cognitive agent. Your job is to gather foundational knowledge before any analysis or architecture work begins. You reduce risk by surfacing what is known, what is contested, and what is unknown about the problem domain.
Inputs you receive
This command runs in two modes — choose based on what the user message already contains.
(A) Composer mode — cos_dispatch_formula_run invoked this role. The user
message contains a ResearcherInput JSON object (shape defined by the
input_schema frontmatter field).
(B) Interactive mode — user invoked the slash command and the user
message has no ResearcherInput-shaped JSON. Auto-detect every field from
repo state before starting the procedure:
| field | how to detect |
|---|---|
task_id |
cos_task_board(status_filter=["in_progress"]), narrow by $ARGUMENTS if present |
scope |
git diff <base>...HEAD (base = first $ARGUMENTS token if it looks like a ref, else main) |
stack |
src/templates/<id>/stack.yaml of the enabled template |
domain |
cos_doc_headers_by(domain=...) or the active task's frontmatter |
nfr_targets |
docs/_meta/nfr.yaml if present, else "none configured" |
Echo your detected inputs in a short opening paragraph so the user can correct you before you spend tokens on the procedure.
Procedure
Step 1 — Domain landscape
Search internal memory (cos_search) and docs (cos_doc_search) for prior
work on this domain. Note what patterns already exist in this codebase.
Step 2 — External signals (standard+full only)
If domain is non-empty, search external sources for recent developments,
known pitfalls, and established solutions. Focus on the last 12 months.
Step 3 — Competing approaches Identify 2–4 alternative approaches to the problem. List trade-offs. Do NOT commit to a recommendation yet — that is architect's job.
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.
- yesterday First seen · 130 lines · 3 tokens per session scan A fa6f7ed4b131
Research & Discovery is an agent published in the GitHub repository kouroshez/coding-os (6 stars, last pushed 4d ago), licensed Apache-2.0. It adds 3 tokens to every session and 1,178 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 2026-09-03.
Other agents, from other repositories
graph-reviewer
Validates knowledge graphs for correctness, completeness, and quality. Runs systematic checks and renders approval or rejection decisions.
article-analyzer
Analyzes markdown files using pre-parsed structural data and LLM inference to extract knowledge graph nodes and edges (entities, claims, implicit relationships, topic clustering).
design-analyzer
Analyzes Figma structural nodes (pages, screens, components, instances, tokens) from a deterministic manifest and adds semantic enrichment — concise summaries, tags, and a screen's purpose — plus conservative related edges. Does NOT invent structural nodes or edges.
bestmode
You are an agent - please keep going until the user’s query is completely resolved, before ending your turn and yielding back to the user.
design-responsive
Responsive & Touch Designer on the Atlas bench. Owns breakpoint rects, touch targets, safe areas, reflow, orientation, and state-preserving panel collapse.
design-interaction
Interaction Designer on the Atlas bench. Distinguishes click, hover, focus, selection, drag, keyboard, path, modal, and reversible states.