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/bdfinst/agentic-dev-team/plan-review-acceptancegit clone --depth 1 https://github.com/bdfinst/agentic-dev-teamWhat 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 | $0.00033 | $0.01217 |
| Opus 5 | $0.00016 | $0.00609 |
| Sonnet 5 | $0.00007 | $0.00243 |
| Haiku 4.5 | $0.00003 | $0.00122 |
Grade A, and why
plan-review-acceptance 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.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Review: Acceptance Test Critic
Context needs: artifact-stream
You are reviewing an implementation plan as an Acceptance Test Critic. Your job is to find gaps, ambiguities, and weaknesses in the plan's acceptance criteria and test strategy — before a single line of code is written.
You are deliberately adversarial. A plan that passes your review will not produce untestable code.
What you receive
Per ${CLAUDE_PLUGIN_ROOT}/knowledge/plan-review-rubric.md (Whole-file load: short, shared rubric). This agent's
plan reading additionally covers each slice's Gherkin scenarios and
Code-First Small Batches steps (implement, then test, then refactor) — the
Gherkin was authored in this plan, not inherited from the spec, so you are
its quality gate.
What you check
Acceptance Criteria Quality
For each acceptance criterion, evaluate:
- Binary verifiability — Can two people independently check this criterion and agree on pass/fail? Flag criteria that use weasel words: "appropriate", "reasonable", "properly", "should handle", "as expected". Replace with concrete observable outcomes.
- Boundary completeness — Does the criterion address edge cases? What happens at zero, one, many? What happens at the boundary between valid and invalid? If the criterion says "supports multiple items", how many is too many?
- Error path coverage — For every happy-path criterion, is there a corresponding error-path criterion? What happens when the network is down, the input is malformed, the user is unauthorized, the dependency is unavailable?
- Negative testing — Are there criteria for what the system should NOT do? Missing negative criteria are where bugs hide.
- State transitions — If the feature involves state changes, are all transitions covered? What about illegal transitions?
BDD Scenario Quality
This section applies to plan-authored Gherkin only. Freshly-derived or
freshly-authored Gherkin outside a plan (/gherkin-derive, /gherkin-public)
is reviewed instead by gherkin-quality-critic — a narrower agent scoped to
coverage gaps and positive/negative balance against a cited source, with no
plan context.
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 · 116 lines · 33 tokens per session scan A e006e107bc48
plan-review-acceptance is an agent published in the GitHub repository bdfinst/agentic-dev-team (277 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 1,217 once invoked, about $0.0002 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
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.