Omnigent is an open-source orchestration layer for running and coordinating different AI coding agents through one system. It is for developers who want to combine agents, apply policies and sandboxing, and continue sessions across devices. The catalogue add-ons extend its agent workflows.
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 omnigent-ai/omnigent --skill resolve-impact-assessmentgit clone --depth 1 https://github.com/omnigent-ai/omnigentWrote 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/omnigent-ai/omnigent/resolve-impact-assessment)<a href="https://agentmods.dev/skills/omnigent-ai/omnigent/resolve-impact-assessment"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/resolve-impact-assessment/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/omnigent-ai/omnigent/resolve-impact-assessment"><img src="https://agentmods.dev/badge/skills/omnigent-ai/omnigent/resolve-impact-assessment.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 | $0.00024 | $0.01274 |
| Opus 5.5 | $0.00010 | $0.00510 |
| Sonnet 5.5 | $0.00005 | $0.00255 |
| Haiku 4.5 | $0.00002 | $0.00127 |
Grade A, and why
resolve-impact-assessment 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 21d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shared impact assessment — every resolution path
Before claiming fixed or approving a PR, check what the full final diff
could break beyond the reported bug. This applies to author, existing-PR review,
ticket-only, and review-remediation modes, including skip_push and
workflow-owned publication. Ticket-only and review-remediation still do not
require an inherited repro; their publication/branch permissions are unchanged.
-
Inspect the candidate and its consumers. Start the assessment while investigating, then refresh it after the last edit. Record the target branch's full tip SHA as
base_shaand the candidate's full HEAD SHA ashead_sha. Inspectgit diff <base_sha>...<head_sha>plus staged, unstaged, and untracked source/test changes. Include configuration, dependencies, and workflows; runtime prompts count as behavior changes even when stored in Markdown. In review modes, inspect the whole PR, not only edits made in this run. Follow shared helpers to their callers and existing tests. For each meaningful risk, identify the changed files, affected behavior, consumers, invariant to preserve, and focused check. A passing original repro is not coverage for every consumer. -
Exercise the relevant boundaries. Select checks from the actual change:
Changed behavior Required focused coverage when applicable Shared startup, configuration, auth, or serialization Existing/default configurations and other affected consumers; exercise configuration creation, transport/decoding, and real process startup together. Correctly constructed objects supplied directly to a unit test do not cover that path. Sandboxing The applicable real OS sandbox with its intended gates enabled. A disabled gate or an unsupported/skipped sandbox test leaves that boundary uncovered. UI state or interaction The reported journey and affected adjacent journeys on the candidate build, including relevant selection, persistence, or reconnect behavior. Environment-derived defaults Ordinary configuration and relevant ambient variables populated; apply the hermetic check in 2B.5. Performance or timing Measure the claimed quantity under the relevant workload. Distinguish simulated-clock tests from elapsed-time measurements; functional success alone does not establish latency or throughput. Use existing tests where they cover the invariant; add a behavioral regression test only for a meaningful gap. Tests of the bug follow their mode's baseline requirements; review-remediation still skips fail-before proof. Checks protecting previously correct behavior may pass on both base and candidate; do not manufacture a failing baseline for them. Run the focused checks for each affected consumer/boundary, even when they live in a different module. Do not run the full repository suite locally. Do not weaken isolation or change global rollout settings to obtain a passing result.
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Record observed results in
impact_assessment. Each risk names its check,result(passed,failed,blocked, ornot_run), and retained evidence. Reference actual command/output or CI run artifacts; include the tested revision/build, dependency pins, and relevant environment/feature gates. Confirm the test imports and exercises this candidate, not another checkout, installed copy, stale SPA, or older CI runtime. Recordworktree_stateascleanonly when the tested source/tests are clean; otherwise name the uncommitted source/test/support files and their content hashes. Artifact-only dirt can be noted separately. A HEAD SHA alone does not identify dirty code.Distinguish component tests, real process/sandbox checks, and live bot checks. An unrun, skipped, xfailed, or setup-failing required check is not a pass: name the missing boundary and reason in
uncovered_boundaries. A large green test count or an unrelated green CI job does not fill that gap. Evidence references describe what was retained; never invent an execution record. -
Refresh before delivery. Re-read the final diff, Git status, and current base/head before every final handoff or review verdict. For an existing PR, compare with the live GitHub base/head SHAs, not just local refs. If the author moved the head, follow the mode's update/retry procedure without approving from old results. After a retry, new PR head, merge/rebase, CI/Polly fix, or changed code, assertions, dependencies, or relevant environment, rebuild the assessment and rerun affected checks. Reuse a result only when its tested contents and context still match; retain its original identity rather than relabeling old evidence as a new execution. Commit hooks can change tested files too. Keep earlier evidence and the saved checkpoint; never reset work to make the identities match.
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Let gaps affect the verdict.
fixedrequires the original behavior to be proven as its mode requires, all identified regression risks checked, and no uncovered required boundary. A discovered regression must be repaired and checked beforefixedor approval. If a fix is only partly verified, preserve the work, usepartially_fixed, and name the failing/unrun checks inremaining_work; useneeds_more_infowhen verification cannot establish a resolution. Setup failures are blockers, not proof of a product regression. A missing recording alone still follows the recording rules below.
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.
- 21d ago First seen · 83 lines · 24 tokens per session scan A ee2fceb13233
resolve-impact-assessment is a skill published in the GitHub repository omnigent-ai/omnigent (10,832 stars, last pushed today), licensed Apache-2.0. It adds 24 tokens to every session and 1,274 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-25.
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