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 skills/panbanda/omen/setup-confignpx skills add panbanda/omen --skill setup-configgit clone --depth 1 https://github.com/panbanda/omenWhat 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 | $0.00028 | $0.02340 |
| Opus 5 | $0.00014 | $0.01170 |
| Sonnet 5 | $0.00006 | $0.00468 |
| Haiku 4.5 | $0.00003 | $0.00234 |
Grade A, and why
setup-config 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.
How it starts
The opening of the file, as written. The whole thing — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup Config
Analyze the current repository and generate an omen.toml configuration tailored to the project's tech stack, test patterns, and feature flag usage.
Workflow
Step 1: Detect Primary Languages
Use Glob to count files by extension:
Glob: **/*.go
Glob: **/*.rb
Glob: **/*.py
Glob: **/*.ts
Glob: **/*.js
Glob: **/*.java
Glob: **/*.rs
Identify the primary language(s) based on file counts. This determines:
- Which exclude patterns to include (language-specific directories)
- Whether to enable cohesion scoring (OO-heavy languages)
Step 2: Detect Feature Flag Providers
Use Grep to search for SDK imports and usage patterns. Add detected providers to feature_flags.providers in the config.
| Provider | Config Value | Search Patterns |
|---|---|---|
| LaunchDarkly | launchdarkly |
launchdarkly, ld-client, LDClient, boolVariation, stringVariation |
| Split | split |
@splitsoftware, splitio, SplitClient, getTreatment |
| Flipper | flipper |
Flipper.enabled?, Flipper[, flipper (in Gemfile) |
| Unleash | unleash |
unleash-client, unleashclient, isEnabled with unleash import |
| Generic | generic |
feature_flag, featureFlag, is_feature_enabled, isFeatureEnabled |
| ENV-based | env |
ENV["FEATURE_, process.env.FEATURE_, os.environ["FEATURE_ |
Also check package manifests:
package.json:launchdarkly-*,@splitsoftware/*,unleash-*Gemfile:launchdarkly-*,flipper,split-*,unleashCargo.toml:launchdarkly,unleashgo.mod:launchdarkly,unleashrequirements.txt/pyproject.toml:launchdarkly-*,split-*,unleashclient
Only include providers that are actually detected. If no providers are found, leave providers = [] with a comment explaining how to add them manually.
Step 2b: Detect Custom Feature Flag Systems
If you find feature flag patterns that don't match the built-in providers, the user likely has an in-house system. Ask them about it and help them create a custom provider.
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.
- 3d ago First seen · 346 lines · 28 tokens per session scan A 31615b10660b
setup-config is a skill published in the GitHub repository panbanda/omen (18 stars, last pushed 10d ago), licensed Apache-2.0. It adds 28 tokens to every session and 2,340 once invoked, about $0.0001 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 2026-08-30.
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