google/mantis is a modular set of security-review skills that coding agents use to find, reproduce, and patch software vulnerabilities. It is for adapting automated security testing to application, infrastructure, machine-learning, hardware, and firmware projects, with expert review required for results. The catalogue skills and instruction provide the workflow for using Mantis with coding agents.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/google/mantisnpx agentmods add skills/google/mantis/mantis-planWrote 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/google/mantis/mantis-plan)<a href="https://agentmods.dev/skills/google/mantis/mantis-plan"><img src="https://agentmods.dev/badge/skills/google/mantis/mantis-plan/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/google/mantis/mantis-plan"><img src="https://agentmods.dev/badge/skills/google/mantis/mantis-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00062 | $0.07377 |
| Opus 5.5 | $0.00025 | $0.02951 |
| Sonnet 5.5 | $0.00012 | $0.01475 |
| Haiku 4.5 | $0.00006 | $0.00738 |
Grade A, and why
mantis-plan 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 1mo 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 — 533 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Strategist (/mantis-plan)
System Goal
Security Architect. Analyzes code structure, directory metadata, and historical records to map the external boundary and formulate an adaptive review roadmap.
Command Definition
- Command:
/mantis-plan - Description: Formulates a targeted defensive security reviewing plan based on the active threat model and historical learnings.
- Arguments (optional; supplied by the orchestrator, consumed by Block A):
--snapshot_root/SNAPSHOT_ROOT: absolute path to the pinned read-only code snapshot (CODE_ROOT for all snapshot-relative paths).--snapshot_id/SNAPSHOT_ID: the pass snapshot identifier (sentinel + Block B comparisons).--state_root: absolute path to theworkspace/state dir (plan.json, .mantis_state.json, findings/, kb/, archive/). STATE-RELATIVE — never prefixed with CODE_ROOT.- All flags absent -> MODE-OFF/legacy mode (Block A step 1d): behaves exactly as today.
Input/Output Contract
- Reads:
workspace/.mantis_state.json(to track current loop pass).workspace/kb/THREAT_MODEL.md(if exists).workspace/kb/index.md(checks existence to determine Mode A vs B).- Mode A: traverses production directories and source files, reads
mantis-summary.md(if available). - Mode B: reads
workspace/kb/index.md,workspace/kb/THREAT_MODEL.md,workspace/archive/.repro_attempts.json(if exists), VCS diffs or file timestamps/hashes. workspace/kb/structural_index/manifest.json(to check structural index availability/status).workspace/helpers/query_structural_index.py(to invoke bounded structural-index queries).workspace/.mantis_state.jsonNEW fields:active_snapshot.{snapshot_id, snapshot_pinned, vcs_type},snapshot_history(read, written by the meta-agent).vcs_typeis read because Block E branches on it. Plan runs Block E in the LIVE repo root to computechanged_files/changed_files_status(COMPUTED or UNKNOWN) and writes them back to state.
- Writes:
workspace/plan.json.- Copies retry-eligible finding JSON files from
workspace/archive/findings_pass_K/orworkspace/archive/loopK_findings/(where K is the pass it was archived in) toworkspace/findings/(preserving their original UUID filenames).
- Preconditions:
- Codebase must be accessible.
- Idempotency Guarantee:
- Overwrites
workspace/plan.jsondirectly. In Mode B, copies a finding back verbatim only when Block B is MATCHED and its file is unchanged and present; otherwise it schedules a fresh re-discovery investigation. Consults.repro_attempts.jsonunder the cache read rule.
- Overwrites
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.
- 1mo ago First seen · 533 lines · 62 tokens per session scan A 8ca2bbd05e4c
mantis-plan is a skill published in the GitHub repository google/mantis (2,454 stars, last pushed yesterday), licensed Apache-2.0. It adds 62 tokens to every session and 7,377 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
ai-prompt-regression-testing
Use when comparing prompt changes against a fixed evaluation set: record actual model settings, required checks, missing results, judge limitations and case-level regression evidence.
review-prs
Review a GitHub pull request in the googleapis/mcp-toolbox repo against the team's reviewer checklist: PR title/description conventions, linked issue, logic errors and unhandled edge cases, breaking changes, test coverage, docs updates, security (input handling), and new dependencies. Use whenever a maintainer asks…
discount-review
Inspect the discount policy fixture with a repeatable review checklist and helper script.
code-review
Reviews code for bugs, security issues, and best practices.
otto-impact-assessment
Check the final diff's consumers, focused tests, evidence, and gaps.
conductor-review
Reviews the completed track work against guidelines and the plan. Acts as a Principal Software Engineer to ensure quality and compliance.