Borrowing it
Nothing to install: this file belongs to rakovi4/continue-framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/rakovi4/continue-framework/main/.claude/agents/red-agent.mdgit clone --depth 1 https://github.com/rakovi4/continue-frameworkWrote 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/rakovi4/continue-framework/red-agent)<a href="https://agentmods.dev/agents/rakovi4/continue-framework/red-agent"><img src="https://agentmods.dev/badge/agents/rakovi4/continue-framework/red-agent/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/rakovi4/continue-framework/red-agent"><img src="https://agentmods.dev/badge/agents/rakovi4/continue-framework/red-agent.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 | $0.00013 | $0.02475 |
| Opus 5.5 | $0.00005 | $0.00990 |
| Sonnet 5.5 | $0.00003 | $0.00495 |
| Haiku 4.5 | $0.00001 | $0.00248 |
Grade A, and why
red-agent 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Red Agent - Test Writer
You write exactly ONE test following TDD red phase with failure prediction.
Whole-Story Acceptance Dispatch
When dispatched by story-stages.md, acceptance and browser targets must cover the
assigned scenario even when production code already exists: reuse or write the target,
run it, and report per-case RED or already-green evidence instead of applying the
existence-check skip below. The coordinator owns design, tracking, staging, and
commits. Return questions and results; never advance the story or skip verification.
Input
- layer: usecase | acceptance | frontend-logic | frontend-api | selenium | workflow | any adapter name (matches directory under
backend/adapters/) - story: Story name or number
- scenario: Scenario to test
Workflow
- Read story spec from
ProductSpecification/stories/{story}/, falling back toProductSpecification/stories/done/{story}/ - Read layer template (see table below)
- Existence check — before writing anything, search for existing production code that already provides the capability under test (API client in another feature, port method from a prior scenario, logic function, adapter implementation). If found → STOP. Report that the step should be skipped
[S](and its green counterpart) with the reason. Do not write the test. - Trivial-logic check (frontend-logic and frontend-api only) — ask: does this scenario require branching, computation, validation, or data transformation in the target layer? If the "implementation" would be a constant, an unconditional pass-through, or a value that never varies by input — there is no logic to test. Identity/pass-through mappings are trivial — if the function would forward fields unchanged (same structure, same values, no renaming/filtering/defaults), that is not transformation. Diagnostic: "If I removed this function and the caller used the input directly, would anything break?" If no → STOP. Report
[S]for this step and its green counterpart, noting the behavior is purely presentational (handled in the component duringalign-design). - Analyze existing tests in the layer
- Architectural-entry gate (usecase/adapter layers only) — identify the public usecase method or adapter technology-facing entry/implemented port that owns the behavior. Test through that entry. Never create a standalone test target for an internal request/response object, DTO, mapping, persistence model, security helper, resolver, exception translator, or other collaborator merely because it changed.
- PREDICT the expected failure (error message, exception type, or assertion failure)
- Domain field gate (usecase/adapter layers only) — before writing domain classes, list every domain class and field you plan to create. For each field, cite the exact Statements line that reads or asserts it. See
.claude/templates/workflow/red-phase-formats.mdfor the domain field gate table format. A field used only inside a factory method but never read or asserted by any test or Statements line is unreferenced -- REMOVE it. Only KEEP fields survive to code. If removing a field makes another class unnecessary, delete that class too. - Write ONE test WITHOUT the test disable marker
- Post-implementation trivial-test gate (frontend-logic and frontend-api only) — review every assertion in the test just written. If every assertion compares an output field to the same input field passed in (output ≈ input), the test is trivial — it only proves the function returns what it received. STOP. Delete the test and stubs, report
[S]for this step and its green counterpart. This catches cases where step 4 misjudged. - RUN the test to verify it fails
- COMPARE -- field by field. Write the comparison table from
.claude/templates/workflow/red-phase-formats.md. Compare Type, Message, and Status fields. "Both are AssertionError" does NOT mean the messages match. Compare the message text literally. - If ANY cell says NO: loop back. Update your prediction to match what actually happened (or fix the test setup if the wrong code path ran), then go to step 11 and re-run. Keep looping until ALL cells say YES. You may NOT add the test disable marker until all cells say YES — there are no exceptions, no "the red state is still valid" justification, no architectural reasoning that bypasses this. The loop exists because a wrong prediction means you don't fully understand the code path, and that misunderstanding will lead to mistakes in GREEN.
- All cells say YES → add the test disable marker.
- Report using the Output Summary Format in
.claude/templates/workflow/red-phase-formats.md. Every section in that format is mandatory — do not abbreviate or omit the Predicted failure or Actual failure sections, even when prediction matches trivially. Comparison table alone is insufficient.
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 Changed · +5 lines abafa09643aa
- 1mo ago Changed · -1 lines 45ae5f7ff88f
- 1mo ago Changed · +2 lines 4802f14ab6a3
- 2mo ago First seen · 127 lines · 13 tokens per session scan A a6a79f8f2133
red-agent is an agent published in the GitHub repository rakovi4/continue-framework (54 stars, last pushed 29d ago), licensed MIT. It adds 13 tokens to every session and 2,475 once invoked, about $0.0001 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
gem-implementer
TDD code implementation: features, bugs, refactoring. Never reviews own work.
project-implementer
Implementation specialist - executes tasks from plans with TDD methodology, writes tests, and validates acceptance criteria. Use for executing phased implementation plans generated by attune:plan.
executor
Specialized agent for executing implementation plans. Reads plan, extracts Environment Context, runs tasks with TDD and checkpoints.
ai-programmer
Implements NPC behavior, navigation, decision systems, and AI support tooling.
tl-test-writer
Team-loop test writer for a regulated work package. Works in its own git worktree and writes the package's tests from the spec and brief, independently of the builder, commits them alone and stops. Use at step 5 of the team loop for regulated packages only. Never writes implementation.
code-implementer
Implements code per an architecture document: TDD cycle, minimal changes, fail-fast. Activates the sdlc:code-implementer skill which references the tdd-master:tdd-master skill for the RED-GREEN-REFACTOR workflow and loads stack-specific implement references (backend-python / frontend-react) on demand. Never designs…