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Sigint

mcp-zircote-sigint · by zircote

Market intelligence toolkit for Claude Code. Iterative research workflows, trend modeling with three-valued logic, multi-format reports, and automated GitHub issue creation from findings.

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Install

$ agentstack add mcp-zircote-sigint

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

sigint - Signal Intelligence

[](https://github.com/anthropics/claude-code) [](LICENSE) [](CHANGELOG.md)

Comprehensive market research toolkit for Claude Code with report generation, GitHub issue creation, and trend-based analysis.

Quick Start

# 1. Start research with a topic
/sigint:start AI-powered code review tools

# 2. Answer elicitation questions (decision context, audience, priorities)

# 3. Check progress
/sigint:status

# 4. Generate report
/sigint:report

# 5. Create GitHub issues (optional)
/sigint:issues

See the [Getting Started Tutorial](docs/tutorials/getting-started.md) for a detailed walkthrough.

Features

  • Swarm-Orchestrated Research: Parallel dimension-analysts coordinate via task system and file-based state
  • Iterative Research Workflow: Start, refine, and finalize market research through commands
  • Multi-Audience Reports: Generate reports for executives, PMs, investors, and developers
  • Trend-Based Modeling: Three-valued logic analysis (INC/DEC/CONST) for uncertain data
  • GitHub Integration: Automatically create sprint-sized issues from findings
  • RLM Large Document Processing: Source-chunker handles documents exceeding context limits
  • Multi-Format Output: Markdown, HTML, Mermaid diagrams

Installation

Claude Code

# Option 1: Plugin Marketplace (recommended)
/plugins add sigint

# Option 2: Local development
claude --plugin-dir /path/to/sigint

# Option 3: Manual install to plugins directory
cp -r sigint ~/.claude/plugins/

Cowork

  1. Open Claude Desktop app > Cowork tab
  2. Click Customize > Browse plugins
  3. Search for "sigint" and click Install

For organization-wide deployment and detailed setup, see the [Cowork deployment guide](docs/how-to/deploy-to-cowork.md).

Commands

| Command | Description | |---------|-------------| | /sigint:start | Begin new research session | | /sigint:augment | Deep-dive into specific area | | /sigint:update | Refresh existing research data | | /sigint:report | Generate comprehensive report | | /sigint:falsify | Adversarially falsify findings (web-only disconfirming search) and remediate (quarantine, downgrade, queue followups) | | /sigint:issues | Create GitHub issues from findings | | /sigint:resume | Resume previous research session | | /sigint:status | Show current research state | | /sigint:init | Initialize plugin configuration |

Agents

  • research-orchestrator: Coordinates parallel dimension-analysts, merges findings
  • dimension-analyst: Focused research on a single dimension (competitive, sizing, trends, etc.)
  • source-chunker: RLM processor for large documents — partitions, analyzes chunks, synthesizes
  • issue-architect: Converts findings to sprint-sized GitHub issues
  • report-synthesizer: Generates multi-format reports with visualizations
  • falsification-analyst: Adversarially attempts to disconfirm findings via web-only search; assigns ordinal verdicts (falsified/weakened/survived/inconclusive)

Skills (Research Methodologies)

Each skill teaches AND executes the methodology:

  1. Competitive Analysis: Porter's 5 Forces, competitor mapping
  2. Market Sizing: TAM/SAM/SOM calculations
  3. Trend Analysis: Macro/micro trend identification
  4. Customer Research: Persona development, needs analysis
  5. Tech Assessment: Technology evaluation, feasibility
  6. Financial Analysis: Revenue models, unit economics
  7. Regulatory Review: Compliance, legal considerations
  8. Report Writing: Executive report best practices
  9. Trend Modeling: Three-valued logic (INC/DEC/CONST), scenario graphs

Report Structure

Reports include:

  • Executive Summary
  • Market Size (TAM/SAM/SOM)
  • Competitive Landscape
  • SWOT Analysis
  • Recommendations
  • Risk Assessment
  • Data Sources & Methodology
  • Transitional Scenario Graphs (Mermaid)

Storage Structure

./reports/
├── README.md                   # Master index of all research
└── topic-name/
    ├── README.md               # Topic research index
    ├── state.json
    ├── YYYY-MM-DD-research.md
    ├── YYYY-MM-DD-report.md
    ├── YYYY-MM-DD-report.html
    ├── YYYY-MM-DD-falsification-report.md
    ├── YYYY-MM-DD-falsification-report.json
    ├── YYYY-MM-DD-falsification-followups.json
    └── YYYY-MM-DD-issues.json

Adversarial Falsification

sigint:falsify treats every finding as a hypothesis under test. It generates disconfirming queries via a hybrid template + LLM-counter-hypothesis strategy, executes web-only adversarial search (no internal memory, no prior findings as evidence), and assigns one of four ordinal verdicts per atomic claim:

| Verdict | Remediation | |---------|-------------| | falsified | Move finding to quarantine.json with gate: "post-falsification"; queue retraction issue | | weakened | Downgrade confidence one level; narrow summary; append disconfirming source; queue follow-up comment on existing issue | | survived | Annotate provenance.falsification_attempts; optional confidence upgrade if multiple credible non-disconfirming sources | | inconclusive | Annotate only |

The skill runs as Phase 3.6 inside the research-orchestrator pipeline (between post-merge codex review and progress rendering) when invoked via /sigint:start or /sigint:update. It can also run standalone:

/sigint:falsify                                 # block-mode, all findings
/sigint:falsify --scope dimension:competitive   # one dimension
/sigint:falsify --scope finding:f_competitive_3 # one finding
/sigint:falsify --mode advisory                 # annotate without halting
/sigint:falsify --query-budget 4 --claim-budget 30

Bounded epistemics: a survived verdict is not proof of truth — it means N adversarial queries per claim were executed without finding disconfirming evidence. The falsification report always includes the actual search budget used so readers can judge how exhaustive the attempt was.

One-round rule: findings that already carry provenance.falsification_attempts from the current session are skipped (no recursive falsification).

Configuration

Configuration uses sigint.config.json (schema v2.0) with project settings overriding global defaults.

Configuration Locations

| Location | Scope | Purpose | |----------|-------|---------| | ./sigint.config.json | Project | Project-specific configuration | | ~/.claude/sigint.config.json | Global | User-wide defaults for all projects |

Resolution order: Project > Global > Built-in defaults

Configuration File Format

Create sigint.config.json at the project root (generated automatically by /sigint:init):

{
  "version": "2.0",
  "defaults": {
    "default_repo": "owner/repo",
    "report_format": "markdown",
    "audiences": ["executives", "product-managers"]
  },
  "research": {
    "maxDimensions": 5,
    "dimensionTimeout": 300,
    "defaultPriorities": ["competitive", "sizing", "trends"]
  },
  "topics": {}
}

> Migrating from legacy config? If you have a sigint.local.md or .sigint.config.json v1.0, run /sigint:migrate to convert.

Dependencies

Required:

  • WebSearch/WebFetch tools for research

Optional:

  • GitHub MCP server or GitHub CLI (gh) for issue creation

References

Primary Research

This plugin's trend modeling methodology is based on:

> Bočková, N., Volná, B., & Dohnal, M. (2025). "Optimisation of complex product innovation processes based on trend models with three-valued logic." arXiv:2601.10768v1. https://arxiv.org/abs/2601.10768

Key concepts adapted from this research:

  • Three-valued logic (INC/DEC/CONST): Minimally information-intensive quantifiers for trend analysis
  • Transitional scenario graphs: Visual representation of possible state transitions
  • Qualitative modeling: Analysis under information scarcity without precise numerical parameters

Frameworks & Methodologies

  • Porter's Five Forces: Porter, M.E. (1979). "How Competitive Forces Shape Strategy." Harvard Business Review, 57(2), 137-145.
  • SWOT Analysis: Learned, E.P., Christensen, C.R., Andrews, K.R., & Guth, W.D. (1965). Business Policy: Text and Cases. Homewood, IL: Irwin.
  • TAM/SAM/SOM: Blank, S. & Dorf, B. (2012). The Startup Owner's Manual. K&S Ranch.

Market Research Methods

  • Competitive Analysis: Fleisher, C.S. & Bensoussan, B.E. (2015). Business and Competitive Analysis: Effective Application of New and Classic Methods. FT Press.
  • Customer Research & Personas: Cooper, A. (1999). The Inmates Are Running the Asylum. Sams Publishing.
  • Technology Assessment: Coates, J.F. (1976). "Technology Assessment." American Scientist, 59(4), 412-418.

Trend Modeling

  • Three-Valued Logic Foundations: Kleene, S.C. (1952). Introduction to Metamathematics. North-Holland.
  • Scenario Planning: Schwartz, P. (1991). The Art of the Long View. Doubleday.

Financial Analysis

  • Unit Economics: Ries, E. (2011). The Lean Startup. Crown Business.
  • Revenue Modeling: Osterwalder, A. & Pigneur, Y. (2010). Business Model Generation. Wiley.

License

MIT

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.