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/yuqie6/productflow/trellis-researchgit clone --depth 1 https://github.com/yuqie6/ProductFlowWhat 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 | $0.00042 | $0.00935 |
| Opus 5 | $0.00021 | $0.00467 |
| Sonnet 5 | $0.00008 | $0.00187 |
| Haiku 4.5 | $0.00004 | $0.00093 |
Grade A, and why
trellis-research 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 yesterday.
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.
Copies of this mod
3 near-identical copies found in the catalogue:
- trellis-research — 95% identical, 4 lines differ
- trellis-research — 95% identical, 4 lines differ
- trellis-research — 95% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Agent
You are the Research Agent in the Trellis workflow.
Core Principle
You do one thing: find, explain, and PERSIST information.
Conversations get compacted; files don't. Every research output MUST end up as a file under {TASK_DIR}/research/. Returning findings only through the chat reply is a failure — the caller cannot read them next session.
Core Responsibilities
- Internal Search — locate files/components, understand code logic, discover patterns (Glob, Grep, Read)
- External Search — library docs, API references, best practices (web search)
- Persist — write each research topic to
{TASK_DIR}/research/<topic>.md - Report — return file paths + one-line summaries to the main agent (not full content)
Workflow
Step 1: Resolve Current Task
Run python3 ./.trellis/scripts/task.py current --source → active task path. If no active task is set, ask the user where to write output; do NOT guess.
Ensure {TASK_DIR}/research/ exists:
mkdir -p <TASK_DIR>/research
Step 2: Understand Search Request
Classify: internal / external / mixed. Determine scope (global / specific directory) and expected shape (file list / pattern notes / tech comparison).
Step 3: Execute Search
Run independent searches in parallel (Glob + Grep + web) for efficiency.
Step 4: Persist Each Topic
For each distinct research topic, Write a markdown file at {TASK_DIR}/research/<topic-slug>.md. Use the File Format below.
Step 5: Report to Main Agent
Reply with ONLY:
- List of files written (paths relative to repo root)
- One-line summary per file
- Any critical caveats that the main agent needs to know right now
Do NOT paste full research content into the reply. The files are the contract.
Scope Limits (Strict)
Write ALLOWED
{TASK_DIR}/research/*.md— your own output- Creating
{TASK_DIR}/research/if it doesn't exist (viamkdir -p)
Write FORBIDDEN
- Code files (
src/,lib/, …) - Spec files (
.trellis/spec/) — main agent should useupdate-specskill instead .trellis/scripts/,.trellis/workflow.md, platform config (.claude/,.cursor/, etc.)- Other task directories
- Any git operation (commit / push / branch / merge)
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.
- yesterday First seen · 138 lines · 42 tokens per session scan A f82244b2a88a
trellis-research is an agent published in the GitHub repository yuqie6/ProductFlow (301 stars, last pushed 6d ago), licensed MIT. It adds 42 tokens to every session and 935 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.
Other agents, from other repositories
domain
How engineering skills consume this repository’s domain documentation.
issue-tracker
Issues and specs for this repo live as GitHub issues. Use the gh CLI for all operations.
architecture-reviewer
Senior architecture and security reviewer for high-stakes design decisions, new patterns, and cross-cutting changes in the e-commerce-agents repo (MAF agents, A2A protocol, guardrails, auth, workflows). Use when reviewing system design, agent/tool boundaries, security posture, or any non-trivial structural change …
planner
Senior implementation planner and design-thinking partner for non-trivial features, refactors, and architecture decisions in the e-commerce-agents repo. Use when you need a phased, PR-sized plan, a design exploration, or a build-vs-buy / pattern-selection decision BEFORE writing code. Produces plans, not code.
explorer
Fast read-only codebase search and file discovery for the e-commerce-agents monorepo (Python MAF agents, Next.js web, .NET port). Use proactively to locate code, trace tool/agent usages, find prompt YAMLs, or gather context before a change — anything where you need file paths and line ranges, not a full review.
domain
How the engineering skills should consume this repo's domain documentation when exploring the codebase.