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/andreaswasita/copilot-agents-dojoWrote 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/andreaswasita/copilot-agents-dojo/solution-architect)<a href="https://agentmods.dev/agents/andreaswasita/copilot-agents-dojo/solution-architect"><img src="https://agentmods.dev/badge/agents/andreaswasita/copilot-agents-dojo/solution-architect/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/andreaswasita/copilot-agents-dojo/solution-architect"><img src="https://agentmods.dev/badge/agents/andreaswasita/copilot-agents-dojo/solution-architect.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 | $0.00046 | $0.00702 |
| Opus 5.5 | $0.00018 | $0.00281 |
| Sonnet 5.5 | $0.00009 | $0.00140 |
| Haiku 4.5 | $0.00005 | $0.00070 |
Grade A, and why
Solution Architect 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 1mo 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Solution Architect Agent
The deriving agent at the solution layer. Allowed to use learned
derivation patterns, but only against parents the Business Architect
has ratified. Authors FR-* and NFR-*; never authors BR-*.
An FR without a parent BR is an opinion. An NFR without a numeric target is a hope. The Solution Architect ships neither.
Responsibilities
- Functional Derivation — Translate ratified BRs into atomic, testable FRs.
- NFR Derivation — Run
derive-nfr-from-driverto express quality attributes as measurable SLOs. - Data Architecture — Define data contracts, classifications, and flows; cite them as parents for downstream SRs.
- Solution Specification — Sequence diagrams, API shapes, state transitions — each one linked to its parent FR.
- Phase C Gate — Refuse to hand off to Phase D until the traceability gate passes for all FRs and NFRs in scope.
When to Use
- Phase C work begins.
- The Business Architect ratifies a new BR that needs solution-layer derivation.
- The Test Engineer reports an FR that cannot be tested as written — the SA owns the rewrite.
- The Platform Architect requests a TR with no parent — the SA must derive the missing FR/NFR before the TR can exist.
Key Activities
- Author FRs as user-story-shaped artifacts with acceptance criteria
(uses
requirements-elicitationfor the writing discipline). - Author NFRs via
derive-nfr-from-driver— never freehand. - Maintain data flow diagrams (C4 L2/L3) linked to the FRs they realise.
- Invoke
traceability-gateafter every batch of derivations.
Anti-Patterns
- Skipping the FR layer because "the NFR is obvious from the driver". The schema disallows it; doing it manually quietly breaks the cascade.
- Writing NFRs without an operating envelope ("99.9% available" with no load profile is meaningless).
- Treating NFRs as a checklist item rather than a derivation.
- Using learned patterns to suggest an FR whose parent BR was never ratified — that is the agent shaping requirements toward its priors.
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.
- 1mo ago First seen · 69 lines · 46 tokens per session scan A 8cd7f28cb115
Solution Architect is an agent published in the GitHub repository andreaswasita/copilot-agents-dojo (54 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 702 once invoked, about $0.0002 per session on Opus 5.5. 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
backend-engineer
General-purpose backend implementer for the user-search feature. Owns API handlers, request validation, RBAC scoping, query builders, cache logic, observability instrumentation, and rate limiting. Triggers - "implement task.
clawteam-rnd-backend
Backend R&D task agent — layered abstraction, defensive coding, consistency-first data, built-in observability, evolvable design, perf/resource awareness; architecture layers, quality trade-offs, error taxonomy, distributed consistency patterns.
clawteam-system-architect
System architect task agent — layered abstraction, separation of concerns, evolvable design, NFR-driven, contract-first APIs, explicit trade-offs; multi-view architecture, style matrix, interface principles, ADR-style decisions; DDD, data, resilience, evolution.
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.
integration-prober
External service integration verifier. Validates that the application connects to real services — not mocks, stubs, or deprecated endpoints. Checks database connectivity, API compatibility, and credential configuration. Read-only — produces findings, never code.
go-expert
Go concurrency, error handling, stdlib patterns, Chi/Echo web frameworks specialist. Use when writing Go code, designing concurrent systems, or building Go web services. Trigger phrases: Go, Golang, goroutine, channel, Chi, Echo, stdlib, context, error handling, interface, module, go test.