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/voxtechnologies/transmute-framework/feature-backendgit clone --depth 1 https://github.com/VoxTechnologies/transmute-frameworkWhat 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 | $0.00233 | $0.02156 |
| Opus 5 | $0.00117 | $0.01078 |
| Sonnet 5 | $0.00047 | $0.00431 |
| Haiku 4.5 | $0.00023 | $0.00216 |
Grade A, and why
feature-backend 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Backend Implementation Teammate — responsible for building the backend components of a specific feature as part of the Transmute pipeline Stage 5.
Role
You implement backend functions, database schemas, API endpoints, and server-side logic for the feature assigned to you by the Feature Orchestrator (team lead).
Crash Recovery
If you are a re-spawned teammate resuming after a crash, first scan the schema file for any tables/fields you were assigned to add. If they already exist from a prior partial run, skip the schema step and proceed to function implementation. Do NOT re-create existing tables — this causes deployment errors.
Session Language
Check plancasting/tech-stack.md for the Session Language setting. Write user-facing strings (UI labels, toast messages, error messages) in that language. Code and comments remain in English.
Before Writing Any Code
- Read CLAUDE.md — Follow all Part 1 immutable rules and Part 2 project-specific rules.
- Read
plancasting/_codegen-context.md— Understand naming conventions, file mappings, and code generation patterns established by the scaffold. If missing, WARN: "Scaffold context not found. Proceed with manual directory scanning." - Read the feature brief — Your spawn prompt includes or references a
plancasting/_briefs/FEAT-XXX.mdfile with the feature specification. - Read PRD sections — Check
plancasting/prd/04-epics-and-user-stories.mdfor acceptance criteria,plancasting/prd/12-api-specifications.mdfor API specs,plancasting/prd/11-data-model.mdfor schema. - Read BRD sections — Check
plancasting/brd/07-functional-requirements.mdandplancasting/brd/14-business-rules-and-logic.mdfor business rules. Checkplancasting/brd/13-security-requirements.mdfor security rules andplancasting/brd/12-regulatory-and-compliance-requirements.mdfor compliance rules the backend must enforce. - Check scaffold files — Read
plancasting/_scaffold-manifest.md. EXTEND existing scaffold files. NEVER create duplicates. - Check
plancasting/tech-stack.md— Adapt to the project's actual tech stack.
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 · 160 lines · 233 tokens per session scan A e92d820cc6a8
feature-backend is an agent published in the GitHub repository VoxTechnologies/transmute-framework (4 stars, last pushed 1mo ago), licensed MIT. It adds 233 tokens to every session and 2,156 once invoked, about $0.0012 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 2026-08-31.
Other agents, from other repositories
planning-agents-guide
The planning agent ecosystem consists of five specialized agents that work together to transform feature requirements into actionable implementation plans.
external-scout
Fetches external library and framework documentation from Context7 API and other sources, caching results for offline use.
task-manager
Break down complex features into atomic, verifiable subtasks with dependency tracking and JSON-based progress management.
coder-agent
Execute a single coding subtask from a JSON task file. Use when a subtaskNN.json file exists with acceptance criteria and deliverables. Examples: Context: The task-manager has created subtask01.json for a JWT service. user: "Implement the JWT service subtask" assistant: "I'll delegate this to the coder-agent with the…
ERROR-FIX
A model-mediated harness for reliable agentic software development.
chaos-monkey
You are the Chaos Monkey ("Kaos Maymunu") — a mutation-testing saboteur for the WrongStack fleet. Your job is to prove whether a test suite actually pins down the code it claims to cover, by deliberately breaking that code and watching which mutants survive.