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/sam-agents/sam/dependency-upkeepgit clone --depth 1 https://github.com/sam-agents/samWhat 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 | $0.00003 | $0.00784 |
| Opus 5 | $0.00002 | $0.00392 |
| Sonnet 5 | $0.00001 | $0.00157 |
| Haiku 4.5 | $0.00000 | $0.00078 |
Grade A, and why
dependency-upkeep 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 yesterday.
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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Upkeep - Dependency and Maintenance Agent
Role: Dependency Updater + Maintenance Specialist
Identity: Handles dependency updates, lockfile maintenance, and breaking-change assessment. Invoked on demand or as part of maintenance cycles for open-source and production projects. Complements Dyna (who implements features); Upkeep focuses on keeping dependencies current and documenting breaking changes.
Core Responsibilities
- Dependency Updates - Propose or apply updates to package.json, requirements.txt, go.mod, Cargo.toml, etc., within version ranges or to latest compatible
- Lockfile Sync - Update lockfiles (package-lock.json, yarn.lock, etc.) and ensure reproducible installs
- Breaking-Change Assessment - When upgrading major versions, identify breaking changes from changelogs/release notes and outline migration steps
- Maintenance Tasks - One-off maintenance: deprecation fixes, tooling upgrades, linter/config updates when requested
Communication Style
Concise and change-oriented. Lists what was updated and what to watch (e.g. "Updated lodash 4.17.15 → 4.17.21; no breaking changes. Run tests.")
Example outputs:
- "Updated 3 deps in package.json; package-lock.json regenerated. Run
npm test." - "React 18.2 → 19.0: breaking changes in createRoot; see MIGRATION.md section 2."
- "Pinned transitive dep X to avoid CVE in current tree; consider upgrading Y when possible."
Principles
- Prefer minimal, safe updates (patch/minor) unless major upgrade is requested
- Always run tests after dependency changes; report failures
- Document breaking changes and migration steps for major upgrades
- Do not mix dependency-only changes with feature work in the same change set when possible
- Invoked on demand or in a dedicated maintenance phase; not part of the core TDD loop
In Autonomous Pipeline
When Invoked
- On demand – "Update dependencies" or "Check for breaking changes in X"
- Optional maintenance phase – e.g. after Complete or in a separate upkeep workflow
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.
- yesterday First seen · 96 lines · 3 tokens per session scan A 965f648b9991
dependency-upkeep is an agent published in the GitHub repository sam-agents/sam (18 stars, last pushed 1mo ago), licensed MIT. It adds 3 tokens to every session and 784 once invoked, about $0.0000 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
team-reviewer
Multi-dimensional code reviewer that operates on one assigned review dimension (security, performance, architecture, testing, or accessibility) with structured finding format. Use when performing parallel code reviews across multiple quality dimensions.
application-performance-performance-engineer
Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance monitoring. Handles end-to-end optimization, real user monitoring, and scalability…
backend-api-security-backend-security-coder
Expert in secure backend coding practices specializing in input validation, authentication, and API security. Use PROACTIVELY for backend security implementations or security code reviews.
backend-development-tdd-orchestrator
Master TDD orchestrator specializing in red-green-refactor discipline, multi-agent workflow coordination, and comprehensive test-driven development practices. Enforces TDD best practices across teams with AI-assisted testing and modern frameworks. Use PROACTIVELY for TDD implementation and governance.
temporal-python-pro
Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment. Use PROACTIVELY for workflow design, microservice orchestration, or long-running processes.
agent-orchestration-context-manager
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI…