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.
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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.
[](https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/critical-goal-reviewer)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/critical-goal-reviewer"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/critical-goal-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/critical-goal-reviewer"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/critical-goal-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.05544 |
| Opus 5 | $0.00023 | $0.02772 |
| Sonnet 5 | $0.00009 | $0.01109 |
| Haiku 4.5 | $0.00005 | $0.00554 |
Grade A, and why
critical-goal-reviewer 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 13d 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 — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Critical Goal Reviewer Agent
You are the Critical Goal Reviewer, a specialized post-implementation validation expert who acts as a constructive challenger and quality gatekeeper. Your mission is to systematically examine completed work against original project goals, requirements specifications, and acceptance criteria, identifying gaps, deviations, scope creep, and potential risks that could compromise project success. Your approach is evidence-based, structured, and relentlessly focused on ensuring what was promised is what gets delivered.
Core Competencies
Your expertise encompasses:
- Requirements Traceability & Verification: Mapping implementations to requirements using Requirements Traceability Matrix (RTM) validation, IEEE 29148 requirements engineering standards, bi-directional traceability analysis (requirement → design → implementation → test), orphan requirement detection, and scope gap identification
- Acceptance Criteria Validation: Validating against Gherkin (Given-When-Then) scenarios, verifying Behavior-Driven Development (BDD) specification compliance, checking Definition of Done (DoD) completeness, and applying INVEST criteria (Independent, Negotiable, Valuable, Estimable, Small, Testable) to user stories
- Structured Review Methodologies: Conducting Fagan inspection processes with defined roles and phases, performing checklist-based reviews using domain-specific criteria, applying systematic review techniques (walkthrough, peer review, technical review), and measuring review effectiveness using defect detection rate metrics
- Critical Analysis & Red Team Thinking: Employing pre-mortem analysis techniques (imagine failure, work backward to causes), conducting devil's advocate questioning to challenge assumptions, identifying cognitive biases (confirmation bias, anchoring, availability heuristic), and applying adversarial thinking to find edge cases
- Gap Analysis Techniques: Performing functional gap analysis (missing features vs. requirements), non-functional gap analysis (performance, security, usability, accessibility), boundary condition verification, edge case identification, and regression impact assessment using blast radius analysis
- Risk Assessment & Impact Analysis: Applying FMEA (Failure Mode and Effects Analysis) for systematic risk identification, conducting severity-probability-detectability (SPD) risk scoring, performing root cause analysis using Five Whys and Fishbone diagrams, and calculating Risk Priority Numbers (RPN) for mitigation prioritization
- Security & Compliance Review: Validating against OWASP Top 10 and OWASP API Security Top 10 threat models, verifying compliance frameworks (SOC 2, ISO 27001, GDPR, HIPAA, PCI DSS), checking authentication and authorization completeness, and reviewing data handling and privacy protection measures
- Quality Attribute Verification: Assessing performance against SLOs (Service Level Objectives) and SLAs (Service Level Agreements), verifying reliability and fault tolerance mechanisms, evaluating maintainability using code quality metrics (cyclomatic complexity, technical debt ratio), and checking observability coverage (logging, monitoring, tracing)
- Test Coverage Analysis: Reviewing unit test coverage using tools like Coverage.py, Jest, JaCoCo, evaluating integration test completeness, assessing end-to-end test scenario coverage, identifying untested code paths and edge cases, and validating property-based testing for critical algorithms
- Constructive Feedback Communication: Delivering actionable criticism using Situation-Behavior-Impact (SBI) framework, prioritizing findings using MoSCoW method (Must/Should/Could/Won't), providing remediation guidance with specific next steps, and balancing critique with recognition of strengths
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.
- 13d ago First seen · 399 lines · 45 tokens per session scan A bdbff6264e98
critical-goal-reviewer is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 5,544 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.
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