oh-my-agent is a harness for checking whether coding agents actually completed their work by verifying tests, required artifacts, independent reviews, and recorded decisions. It is used across multiple agent runtimes to make workflow results auditable instead of relying on an agent's own report. The catalogue add-ons provide parts of its skills, agents, hooks, MCP integrations, instructions, and plugins.
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 first-fluke/oh-my-agent --skill oma-scholargit clone --depth 1 https://github.com/first-fluke/oh-my-agentWrote 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/first-fluke/oh-my-agent/oma-scholar)<a href="https://agentmods.dev/skills/first-fluke/oh-my-agent/oma-scholar"><img src="https://agentmods.dev/badge/skills/first-fluke/oh-my-agent/oma-scholar/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/first-fluke/oh-my-agent/oma-scholar"><img src="https://agentmods.dev/badge/skills/first-fluke/oh-my-agent/oma-scholar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00073 | $0.03691 |
| Opus 5 | $0.00036 | $0.01845 |
| Sonnet 5 | $0.00015 | $0.00738 |
| Haiku 4.5 | $0.00007 | $0.00369 |
Grade A, and why
oma-scholar scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://knows.academy/api/proxy/search?q=..." Copies of this mod
2 near-identical copies found in the catalogue:
- oma-scholar — 100% identical, 18 lines differ
- oma-scholar — 91% identical, 60 lines differ
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scholar - Research Paper Sidecar Companion
Scheduling
Goal
Search, fetch, generate, validate, analyze, review, and compare scholarly paper sidecars using the Knows .knows.yaml spec for token-efficient research workflows.
Intent signature
- User asks for academic literature search, sidecar generation, sidecar validation, paper claims/evidence summary, structural paper comparison, or peer review as sidecar.
- User references Knows,
.knows.yaml, knows.academy, OpenAlex, claims, evidence, relations, or paper sidecars.
When to use
- Reading research papers token-efficiently via Knows sidecars (~700 tokens for claims-only vs ~10K for full PDF)
- Generating
.knows.yamlsidecars from your own paper drafts, LaTeX, or research notes - Validating sidecar structure (rule-based) before sharing
- Producing peer reviews as sidecars
- Querying or summarizing existing sidecars
- Structurally comparing two papers (claims, methods, evidence)
- Searching/fetching sidecars from
knows.academy(2026 papers only; current counts via/api/proxy/jobs/stats)
When NOT to use
- General web search or non-academic content -> use
oma-search - Translating papers -> use
oma-translation - PDF parsing only (no sidecar) -> use
oma-pdf - Submitting sidecars back to knows.academy -> out of scope (host LLM only consumes/produces locally)
- Full peer-review workflow with editor system -> out of scope
Expected inputs
- Paper, abstract, draft, LaTeX, research notes, sidecar file, DOI, OpenAlex ID, Knows record ID, or search query
- Desired mode: generate, validate, review, analyze, compare, or remote fetch
- Optional strictness, section filter, or CI behavior
Expected outputs
.knows.yamlsidecar, review sidecar, lint report, search/fetch result, natural-language analysis, or structural comparison- Sidecars conforming to v0.9.0 /
paper@1profile - Validation status and warnings before sharing generated sidecars
Dependencies
oma scholarCLI subcommands- knows.academy public API; OpenAlex and Semantic Scholar fallbacks
resources/sidecar-spec.md, API endpoints, OpenAlex setup, upstream cache, checklist, and execution protocol
What ships with it
8 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.
- 2d ago Changed · -6 lines 0ad3c16cb9a2
- 12d ago First seen · 285 lines · 73 tokens per session scan A 2c722bc5672e
oma-scholar is a skill published in the GitHub repository first-fluke/oh-my-agent (1,286 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 3,691 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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ai-fleet-project-execution
AI fleet project execution (orchestrator=PM, marketing agent, backend dev agent, video agent). Fast-iteration architecture pivots and inter-agent task delegation across multi-hour sessions. Use when a user assigns a multi-agent project with "take it as a team" instruction.
memoria-heartbeat
Minden körben átnézi az ELŐZŐ KÖR ÓTA történteket, menti a fontosat, és skill-eket generál ha volt komplex munka.
github-pr-rebase-merge
Merge a stack of GitHub PRs sequentially when they share files and will cause cascading conflicts. Triggers when user says "merge the PRs sorban" or similar, and the PRs come from external forks (cannot push back to PR branch).
handoff
Generate a HANDOFF.md context transfer document for session continuity. Use when switching sessions, handing off to another agent, or preserving complex task context before a context window reset. Trigger on "/handoff" command or "handoff:" prefix in inter-agent messages.
approval-request-handling
A fő-ágens eljárása, amikor egy sub-ágens jóváhagyást kér az approval API-n keresztül ([APPROVALREQUEST] inter-agent üzenet). Kiküldi a kérést a tulajdonosnak, feldolgozza a szöveges válaszát, és lezárja az approvalt. Akkor használd, ha [APPROVALREQUEST] kezdetű inter-agent üzenetet kapsz.