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/google/mantis/mantis-configurenpx skills add google/mantis --skill mantis-configuregit clone --depth 1 https://github.com/google/mantisWhat 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 | $0.00077 | $0.01706 |
| Opus 5 | $0.00039 | $0.00853 |
| Sonnet 5 | $0.00015 | $0.00341 |
| Haiku 4.5 | $0.00008 | $0.00171 |
Grade A, and why
mantis-configure 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 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.
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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline Configurator (/mantis-configure)
System Goal
Environment and Model Configurator. Configures workflow.json with appropriate
sandbox execution mechanisms, AI model providers, API endpoints, and credential
bindings. Provides instantaneous preflight verification to guarantee that LLM
credentials and sandbox isolation requirements are fully operational before
launching security review campaigns.
Command Definition
- Command:
/mantis-configure - Description: Configures Mantis pipeline settings (sandboxes, models,
credentials, preflight validation) in
workflow.json. - Execution Command:
# From reference/ directory: python3 scripts/configure.py [flags...] # From repository root: python3 reference/scripts/configure.py [flags...] - CLI Options:
--sandbox/-s: Sandbox mechanism (static-only,gvisor,microsandbox,gce).--model/-m: Default LLM model (e.g.gemini-3.7-flash,vertex_ai/claude-opus-5,vertex_ai/zai_org/glm-5.2-maas,openai/{MODEL_ID}).--api-base: Custom endpoint URL for OpenAI-compatible LLM servers (e.g.http://localhost:8000/v1).--reasoning-effort: Reasoning effort level (low,medium,high).--timeout: LLM request timeout in seconds.--project/-p: GCP Project ID (for GCE sandbox or Vertex AI routing).--zone/-z: GCP Zone (e.g.us-central1-b).--image/-i: Sandbox image name (e.g.mantis-sandbox-imageormantis-sandbox:latest).--subnet: GCE Subnet name (e.g.mantis-isolated-subnet).--workdir: Sandbox guest workdir (default:/workspace).--workflow/-w: Path toworkflow.json(defaults to auto-discovery).--db/-d: Path to SQLite knowledge database (default:knowledge.db).--auto: Auto-detects host capabilities and configures optimal settings automatically.--save: Explicitly saves configuration changes toworkflow.local.json.--save-tracked/--global: Saves configuration changes directly to baseworkflow.json.--interactive: Interactive step-by-step terminal wizard.--test/--preflight: Executes fast (1-2s) validation tests verifying LLM reachability and sandbox readiness.--show: Displays current configuration and diagnostic status.--dry-run: Simulates configuration changes without modifying files.--update-nodes: Updates all agent nodes inworkflow.jsonto use the specified default model.--json: Outputs configuration status and preflight diagnostics in JSON.
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 First seen · 175 lines · 77 tokens per session scan A 16e191ace4eb
mantis-configure is a skill published in the GitHub repository google/mantis (853 stars, last pushed 5d ago), licensed Apache-2.0. It adds 77 tokens to every session and 1,706 once invoked, about $0.0004 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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