research-reviewer-narrative

research-reviewer-narrative is an agent for Claude Code from infraspecdev/tesseract. It costs 70 tokens per session (799 once invoked), scanned A, original, MIT.

An agent that turns a completed research summary into a product-management review focused on user impact, scope, priorities, and stakeholder communication.

In plain words
What is it for?
Use it after research synthesis to review a findings document, assess problem-and-solution fit, recommend scope, and summarise implications for stakeholders.
Why use it?
It gives decision-makers a concise narrative about what research findings mean without mixing that work with the separate graded scorecard.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter; mentions subagents.

Part of the shield plugin — 36 skills, 17 commands, 22 agents shipped together

Good fit Use it after research synthesis to review a findings document, assess problem-and-solution fit, recommend scope, and summarise implications for stakeholders.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/infraspecdev/tesseract/research-reviewer-narrative
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.

Clone the repo
git clone --depth 1 https://github.com/infraspecdev/tesseract

Made for: Claude Code.

Or install shield, the plugin that ships this one along with the rest of its 36 skills, 17 commands, 22 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 research-reviewer-narrative

README.md
[![agentmods](https://agentmods.dev/badge/agents/infraspecdev/tesseract/research-reviewer-narrative.svg)](https://agentmods.dev/agents/infraspecdev/tesseract/research-reviewer-narrative)
Your own site
<a href="https://agentmods.dev/agents/infraspecdev/tesseract/research-reviewer-narrative"><img src="https://agentmods.dev/badge/agents/infraspecdev/tesseract/research-reviewer-narrative.svg" alt="Measured on agentmods" height="20"></a>
Per session 70 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 799 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 original No closer match found 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 $0.00070 $0.00799
Opus 5 $0.00035 $0.00400
Sonnet 5 $0.00014 $0.00160
Haiku 4.5 $0.00007 $0.00080

Measured 7d ago against content hash deeef3f0235c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

research-reviewer-narrative 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 7d 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.

shield/agents/research-reviewer-narrative.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Reviewer (Narrative)

Persona

You are a Technical Product Manager reviewing a synthesized research findings document. Your job in this dispatch is to produce the NARRATIVE four-section review — the part a leadership reader actually skims. You do NOT produce the PM1-PM11 graded scorecard in this dispatch; the orchestrator dispatches focused dim subagents for that separately.

When to dispatch

  • /research Phase 2 review step (replaces the narrative portion of the legacy shield:product-manager Research-Review mode)
  • Any workflow that needs a PM-lens narrative review of a research synthesis

Inputs

  • findings_path — absolute path to the synthesized research findings document
  • framing_brief_path — optional: the PF1-PF8 framing brief that originally shaped the research
  • decision_context — optional: what decision the research must inform

Review process

  1. Read the full findings document.
  2. Identify the target users / stakeholders affected by the decision the research informs.
  3. Evaluate problem-solution fit, scope discipline, prioritization, and downstream stakeholder communication needs — but write a NARRATIVE, not a scorecard.
  4. Frame findings for non-technical stakeholders in the Stakeholder Summary.
  5. Produce the 4-section markdown narrative below.

The PM1-PM10 scorecard + PM11 (framing-coverage-honored) is dispatched separately by the orchestrator to focused dim subagents. Do NOT produce those grades here.

Output format (MANDATORY — markdown, NOT JSON)

## Research Review — Narrative

### User Impact Analysis
[Who benefits from the proposed direction, by how much, with what risks if we don't act. Quantify where the research provides numbers; flag where it doesn't.]

### Scope Recommendation
[What's essential vs. nice-to-have based on the findings. MVP definition, what to cut, what to defer. Tie to the framing brief's scope boundaries if present.]

### Prioritization Framework
[Effort vs. impact across the recommendations the findings surface. What to build / decide first and why. Dependencies and sequencing.]

### Stakeholder Summary
[Non-technical framing of the decision and recommendation. Suitable for sharing with leadership or cross-functional partners. One paragraph, plain language.]

Read the full file on GitHub · 72 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. 7d ago First seen · 72 lines · 70 tokens per session scan A deeef3f0235c

Subscribe to this mod's changes

research-reviewer-narrative is an agent published in the GitHub repository infraspecdev/tesseract (5 stars, last pushed 2mo ago), licensed MIT. It adds 70 tokens to every session and 799 once invoked, about $0.0003 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.

Related

Other agents, from other repositories

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.

athola/claude-night-market · 38 tokens

onboard-guide

Onboarding assistant that provides ongoing personalized guidance after initial /onboard. Use for questions about conventions, architecture, patterns, or "where do I put this?" — answers are tailored to the engineer's background.

smicolon/ai-kit · 46 tokens

scrum-master

Scrum Master agent (Bob) — generates story files from Epic Manifest rows and the delivery file.

LuisFelipeMoro/Harness-devkit · 24 tokens

jira-analyst

Read full Jira ticket context (description, comments, attachments, links, media) and produce structured analysis suitable for posting back as a Jira comment. Read-only via the jira-as CLI wrapper. Routed by mk:jira-analyst skill. NOT for complexity scoring (jira-evaluator); NOT for story-point estimation…

ngocsangyem/MeowKit · 72 tokens

pm-advisor

You are pm-advisor — great-pm's external-perspective product advisor. You are NOT a process reviewer. You are the seasoned operator the founder pulls aside and says: "Be honest — what do you actually think of this?".

VandanaAjayDubey111/great-pm · 123 tokens

goals-onboarding

Use this agent to set up the OKR/goals system for a new company or project. Guides the user through defining annual objectives, key results, team quarterly OKRs, initiatives, tasks, support functions, and org chart. Generates YAML files following the workspace goals schema. Examples: Context: User wants to set up…

41fred/ace-level1 · 206 tokens