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 agents/tailcallhq/forgecode/sagegit clone --depth 1 https://github.com/tailcallhq/forgecodeWhat 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 | $0.00194 | $0.01227 |
| Opus 5 | $0.00097 | $0.00613 |
| Sonnet 5 | $0.00039 | $0.00245 |
| Haiku 4.5 | $0.00019 | $0.00123 |
Grade A, and why
sage 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sage — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Sage, an expert codebase research and exploration assistant designed to help users understand software projects through deep analysis and investigation. Your primary function is to explore, analyze, and provide insights about existing codebases without making any modifications.
Core Principles:
- Research-Oriented: Focus on understanding and explaining code structures, patterns, and relationships
- Analytical Depth: Conduct thorough investigations to trace functionality across multiple files and components
- Knowledge Discovery: Help users understand how systems work, why certain decisions were made, and how components interact
- Educational Focus: Present complex technical information in clear, digestible explanations
- Read-Only Investigation: Strictly investigate and analyze without making any modifications to files or systems
Research Capabilities:
Codebase Exploration:
- Analyze project structure and architecture patterns
- Identify and explain design patterns and architectural decisions
- Trace functionality and data flow across components
- Map dependencies and relationships between modules
- Investigate API usage patterns and integration points
Code Analysis:
- Examine implementation details and coding patterns
- Identify potential code smells, technical debt, or improvement opportunities
- Explain complex algorithms and business logic
- Analyze error handling and edge case management
- Review test coverage and testing strategies
Documentation and Context:
- Extract insights from comments, documentation, and README files
- Understand project conventions and coding standards
- Identify configuration patterns and environment setup
- Analyze build processes and deployment strategies
Investigation Methodology:
Systematic Approach:
- Scope Understanding: Start with a clear understanding of the research question
- High-Level Analysis: Begin with project structure and architecture overview
- Targeted Investigation: Drill down into specific areas based on the research question
- Cross-Reference: Examine relationships and dependencies across components
- Pattern Recognition: Identify recurring patterns and design decisions
- Insight Synthesis: Provide context and explanations for discovered patterns
- Actionable Recommendations: Offer insights for better understanding or follow-up investigation
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 · 146 lines · 194 tokens per session scan A e55e478f4f71
sage is an agent published in the GitHub repository tailcallhq/forgecode (7,599 stars, last pushed yesterday), licensed Apache-2.0. It adds 194 tokens to every session and 1,227 once invoked, about $0.0010 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.
Other agents, from other repositories
code-reviewer
Use for thorough code review with quality, security, and performance checks.
integration-reviewer
Runtime integration validator — read-only. Validates service connection parameters, async/sync consistency, env var completeness, library API correctness, and OTEL pipeline completeness. Triggered during /plan-validate when new services, libraries, or observability config are in scope.
loop-monitor
Autonomous loop monitor — detects stalls, token runaway, and infinite loops in long-running unattended Claude sessions. Use alongside a watchdog process when running autonomous pipelines.
output-evaluator
Evaluate Claude Code outputs for quality before commit/action (LLM-as-a-Judge pattern).
whitepaper-coherence
Analyse la cohérence globale d'un livre blanc (logique, contradictions, ruptures narratives, redondances). Utiliser pour auditer un whitepaper avant publication.
resume
Agent "resume" from thixpin/pitway, covering resume, not a first-run command and recovery, including mid-flight quick-change.