ensemble-full-refine-trd

ensemble-full-refine-trd is a skill for Claude Code from FortiumPartners/ensemble. It costs 45 tokens per session (3,097 once invoked), scanned A, a copy of ensemble-refine-trd, MIT.

A process for improving an existing Technical Requirements Document (TRD), a document describing how software should be built. It reviews feedback, research, and gaps while keeping version history and links between requirements and design.

In plain words
What is it for?
Use it to review a TRD, identify missing or weak sections, update its requirements, and assess whether the design is ready.
Why use it?
It helps find incomplete or inconsistent technical decisions without starting implementation. It also lets the user choose which suggested improvements should be applied.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Part of the ensemble-pi plugin — 7 skills, 6 agents shipped together

Good fit Use it to review a TRD, identify missing or weak sections, update its requirements, and assess whether the design is ready.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/fortiumpartners/ensemble/ensemble-full-refine-trd
Install

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.

Any agent
npx skills add FortiumPartners/ensemble --skill ensemble-full-refine-trd
Clone the repo
git clone --depth 1 https://github.com/FortiumPartners/ensemble

Made for: Claude Code.

Or install ensemble-pi, the plugin that ships this one along with the rest of its 7 skills, 6 agents.

Wrote 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.

agentmods badge for ensemble-full-refine-trd

README.md
[![agentmods](https://agentmods.dev/badge/skills/fortiumpartners/ensemble/ensemble-full-refine-trd/github.svg)](https://agentmods.dev/skills/fortiumpartners/ensemble/ensemble-full-refine-trd)
Your own site
<a href="https://agentmods.dev/skills/fortiumpartners/ensemble/ensemble-full-refine-trd"><img src="https://agentmods.dev/badge/skills/fortiumpartners/ensemble/ensemble-full-refine-trd/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.

agentmods 80×15 button for ensemble-full-refine-trd

Your own site · 80×15
<a href="https://agentmods.dev/skills/fortiumpartners/ensemble/ensemble-full-refine-trd"><img src="https://agentmods.dev/badge/skills/fortiumpartners/ensemble/ensemble-full-refine-trd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,097 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.03097
Opus 5 $0.00023 $0.01548
Sonnet 5 $0.00009 $0.00619
Haiku 4.5 $0.00005 $0.00310

Measured 6d ago against content hash 67459442bd7f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ensemble-full-refine-trd 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 6d 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.

Origin

This is a copy

91% identical to ensemble-refine-trd — 184 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

packages/pi/skills/ensemble-full-refine-trd/SKILL.md · 214 lines

How it starts

The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ensemble:refine-trd

Mission: Refine and enhance an existing Technical Requirements Document based on stakeholder feedback, additional research, or identified gaps. Updates TRD while maintaining version history, traceability, and Design Readiness scoring.

Constraints:

  • DO NOT implement, build, or execute any technical work described in the TRD
  • This command ONLY refines the TRD document itself
  • The arguments describe what should be improved in the document, not what should be built
  • After refining the TRD, stop and wait for user approval before any implementation
  • DO NOT make any edits during Synthesis -- findings are presented first, edits happen only after user selects items

Phase 1: TRD Review

Step 1: Current TRD Analysis

Review existing TRD content and extract structural metadata

Actions:

  1. Read the TRD file from the path provided in $ARGUMENTS
  2. Parse frontmatter for Document ID (TRD-YYYY-NNN), Version, PRD reference, Design Readiness Score
  3. Count total tasks (TRD-NNN pattern), total test tasks (TRD-NNN-TEST), total hours estimated
  4. Build dependency graph from [depends: TRD-NNN] annotations
  5. Check if Acceptance Criteria Traceability matrix exists
  6. Note current version number for bumping later
  7. PR format detection: scan TRD for '### PR ' followed by a digit within the '## Master Task List' section (from '## Master Task List' heading to the next '##' heading or EOF). If found: set PR_FORMAT=true and log 'TRD format: PR-stack'. Else: set PR_FORMAT=false and log 'TRD format: legacy phase/sprint'.
  8. If PR_FORMAT=true: count PR boundary sections; for each ### PR N: heading check whether a Shippable State: line immediately follows it; record MISSING_SHIPPABLE[N] for any that don't; record INFRA_ONLY_SHIPPABLE[N] for any whose Shippable State text contains only infrastructure language (e.g., 'scaffolding', 'setup done', 'infrastructure complete') with no user-observable capability.

Read the full file on GitHub · 214 lines

Changes

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.

  1. 6d ago First seen · 214 lines · 45 tokens per session scan A 67459442bd7f

Subscribe to this mod's changes

ensemble-full-refine-trd is a skill published in the GitHub repository FortiumPartners/ensemble (12 stars, last pushed 2d ago), licensed MIT. It adds 45 tokens to every session and 3,097 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to ensemble-refine-trd, differing in 184 lines, and is treated as a copy.

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