Audits production source code files based on the strategy in workspace/plan.json. Use when a review plan exists and you need to perform static analysis and deep-dive reviews of targeted files. Don't use for planning, deduplicating, or writing patches.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmantis-researcherExecute the skills CLI command in your project's root directory to begin installation:
Fetches mantis-researcher from google/mantis and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate mantis-researcher. Access via /mantis-researcher in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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| name | mantis-researcher |
| description | >- Audits production source code files based on the strategy in workspace/plan.json. Use when a review plan exists and you need to perform static analysis and deep-dive reviews of targeted files. Don't use for planning, deduplicating, or writing patches. |
Resilience Code Auditor. Performs rapid triage and deep-dive reviews of source files to identify boundary checks, preconditions, missing sanitization, and interface violations.
/mantis-researcherworkspace/plan.json.workspace/plan.json (falls back to codebase sweep if missing/empty).workspace/.mantis_state.json (to track current loop pass)."kb_references" (e.g.
workspace/kb/entities/*.md).workspace/findings/<uuid>.json (creates
workspace/findings/ if missing).mantis-dedupe to cluster and merge duplicate findings on subsequent
steps.Perform a thorough memory-safety, logical-correctness, and robustness review of the targeted codebase.
Execute the research stage as follows:
Load Reviewing Plan & Context: Read the active pass number from
workspace/.mantis_state.json and resolve the current ISO 8601 timestamp.
Read the workspace/plan.json file to retrieve the target investigations.
If workspace/plan.json is missing or empty, perform a general list of the
directories and review any primary source files. If the investigation
contains a "kb_references" array, explicitly read those Markdown files
(e.g., workspace/kb/entities/auth.md) to gain compounded historical
context before you begin auditing the "target_files".
Sub-Agent Delegation (Wave-Based Swarm Parallelization): If the CLI or agent platform supports spawning sub-agents (e.g., using specialized sub-agent tools or multi-agent orchestrator directives):
workspace/plan.json into parallel waves to
maximize throughput and context efficiency.workspace/plan.json. Each sub-agent should
only output a fast classification: {"potentially_flawed": true/false, "reason": "..."}.workspace/findings/<id>.json files on disk. Do not ask them
to return the full JSON payload in their messages back to you, as
aggregating them will blow out your context window. Ask them to only
return the list of UUIDs they created.Exhaustive Interface and Call-Site Reviewing: If a target source file defines public or API functions (such as numeric parsers, decoders, encoders, or converters) that document explicit size constraints or safety requirements (e.g., expecting callers to allocate buffers of a certain size):
Unconstrained / Exploratory Investigations: If the investigation plan in
workspace/plan.json contains instructions or a question explicitly asking
for an unconstrained sweep or adversarial audit (ignoring existing
assumptions):
workspace/kb/THREAT_MODEL.md.Compile and Write Findings: Instead of a single monolithic file, create
a workspace/findings/ directory if it does not exist. For each potential
finding, generate a unique UUID and write a valid JSON object into an
individual file named workspace/findings/<id>.json. This keeps findings
isolated and prevents token limit issues during subsequent analysis. Do not
include any text before or after the JSON in the files.
{
"id": "A unique identifier generated for this finding (e.g., a UUID or random hash). This must be included and match the filename.",
"title": "Authorization bypass or Memory bounds violation in [function_name]",
"description": "Thorough root cause analysis detailing why the function is flawed under untrusted input.",
"impact": "Exploit outcome (e.g., Privilege escalation, Memory corruption, Data exfiltration).",
"severity": "CRITICAL / HIGH / MEDIUM / LOW",
"privileges_required": "NONE / LOW / HIGH",
"attacker_position": "EXTERNAL / INTERNAL_NETWORK / IN_CLUSTER / LOCAL / HOST_SYSTEM / SUPPLY_CHAIN / PHYSICAL_TEMPORARY / PHYSICAL_LONG_TERM",
"user_interaction": "NONE / REQUIRED",
"status": "PROVISIONALLY_VALID",
"code_paths": ["relative/file/path.c:line_number"],
"mitigation": "Recommended corrective modification.",
"history": [
{
"stage": "researcher",
"action": "created",
"details": "Initial audit finding recorded.",
"pass_number": <current_pass_number>,
"timestamp": "<current_iso8601_timestamp>"
}
]
}
Ensure all individual finding files are written to the workspace/findings/
directory. When complete, notify the user.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
mantis-researcher reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for mantis-researcher matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in mantis-researcher — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend mantis-researcher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
mantis-researcher reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend mantis-researcher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in mantis-researcher — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for mantis-researcher matched our evaluation — installs cleanly and behaves as described in the markdown.
mantis-researcher reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for mantis-researcher matched our evaluation — installs cleanly and behaves as described in the markdown.
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