dependency-expert

dependency-expert is a command for Codex from Orinks/AccessiWeather. It costs 10 tokens per session (1,568 once invoked), scanned A, original, MIT.

A guide for evaluating third-party packages, software development kits, and service APIs before adding them to a project.

In plain words
What is it for?
It helps compare maintenance activity, usage, licensing, security history, API quality, documentation, version compatibility, and replacement options using evidence.
Why use it?
It reduces the risk of choosing an abandoned, insecure, poorly documented, incompatible, or legally unsuitable dependency.

Command for Codex

Install

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.

agentmods
npx agentmods add commands/orinks/accessiweather/dependency-expert
Clone the repo
git clone --depth 1 https://github.com/Orinks/AccessiWeather

Made for: Codex.

Wrote 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.

agentmods badge for dependency-expert

README.md
[![agentmods](https://agentmods.dev/badge/commands/orinks/accessiweather/dependency-expert.svg)](https://agentmods.dev/commands/orinks/accessiweather/dependency-expert)
Your own site
<a href="https://agentmods.dev/commands/orinks/accessiweather/dependency-expert"><img src="https://agentmods.dev/badge/commands/orinks/accessiweather/dependency-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 10 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,568 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00010 $0.01568
Opus 5 $0.00005 $0.00784
Sonnet 5 $0.00002 $0.00314
Haiku 4.5 $0.00001 $0.00157

Measured 4d ago against content hash 643bc342ffe0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dependency-expert 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 4d 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.

.codex/prompts/dependency-expert.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adopting the wrong dependency creates long-term maintenance burden and security risk. These rules exist because a package with 3 downloads/week and no updates in 2 years is a liability, while an actively maintained official SDK is an asset. Evaluation must be evidence-based: download stats, commit activity, issue response time, and license compatibility.

<ask_gate>

  • Default to outcome-first, evidence-dense outputs; include the result, evidence, validation or uncertainty, and stop condition without padding.
  • Treat newer user task updates as local overrides for the active task thread while preserving earlier non-conflicting criteria.
  • If correctness depends on more reading, inspection, verification, or source gathering, keep using those tools until the evaluation is grounded. </ask_gate>

<execution_loop> <success_criteria>

  • Evaluation covers: maintenance activity, download stats, license, security history, API quality, documentation
  • Each recommendation backed by evidence (links to npm/PyPI stats, GitHub activity, etc.)
  • Version compatibility verified against project requirements
  • Migration path assessed if replacing an existing dependency
  • Risks identified with mitigation strategies </success_criteria>

<verification_loop>

  • Default effort: medium (evaluate top 2-3 candidates).
  • Quick lookup (LOW tier): single package version/compatibility check.
  • Comprehensive evaluation (STANDARD tier): multi-candidate comparison with full evaluation framework.
  • Stop when recommendation is clear and backed by evidence.
  • Continue through clear, low-risk next steps automatically; ask only when the next step materially changes scope or requires user preference. </verification_loop>

<tool_persistence>

  • Use WebSearch to find packages and their registries.
  • Use WebFetch to extract details from npm, PyPI, crates.io, GitHub.
  • Use Read to examine the project's existing dependency manifests (package.json, requirements.txt, etc.) for compatibility context. </tool_persistence> </execution_loop>

Read the full file on GitHub · 130 lines

Changes

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.

  1. 4d ago First seen · 130 lines · 10 tokens per session scan A 643bc342ffe0

Subscribe to this mod's changes

dependency-expert is a command published in the GitHub repository Orinks/AccessiWeather (24 stars, last pushed 10d ago), licensed MIT. It adds 10 tokens to every session and 1,568 once invoked, about $0.0001 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.