roundtrip-radar

roundtrip-radar is a skill for Claude Code from Terryc21/radar-suite. It costs 73 tokens per session (16,394 once invoked), scanned A, original, Apache-2.0.

A workflow audit tool that follows data through complete user journeys in an application. A journey might be creating an item, saving it, displaying it, and editing it later.

In plain words
What is it for?
It helps discover workflows, trace a chosen journey, audit one workflow at a time, summarize issues shared across workflows, and compare results with an earlier audit.
Why use it?
It finds bugs, data-safety risks, performance problems, and missing steps that can be overlooked when each screen or function is checked separately.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool; mentions Claude Code.

Part of the radar-suite plugin — 8 skills shipped together

Good fit It helps discover workflows, trace a chosen journey, audit one workflow at a time, summarize issues shared across workflows, and compare results with an earlier audit.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/terryc21/radar-suite/roundtrip-radar
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 Terryc21/radar-suite --skill roundtrip-radar
Clone the repo
git clone --depth 1 https://github.com/Terryc21/radar-suite

Made for: Claude Code.

Or install radar-suite, the plugin that ships this one along with the rest of its 8 skills.

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 roundtrip-radar

README.md
[![agentmods](https://agentmods.dev/badge/skills/terryc21/radar-suite/roundtrip-radar.svg)](https://agentmods.dev/skills/terryc21/radar-suite/roundtrip-radar)
Your own site
<a href="https://agentmods.dev/skills/terryc21/radar-suite/roundtrip-radar"><img src="https://agentmods.dev/badge/skills/terryc21/radar-suite/roundtrip-radar.svg" alt="Measured on agentmods" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 16,394 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 11 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high System Prompt Leakage · line 190
    Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.
    Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
  • high System Prompt Leakage · line 210
    Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.
    Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
  • high System Prompt Leakage · line 222
    Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.
    Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
  • high System Prompt Leakage · line 210
    Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.
    Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
  • medium Agent Snooping · line 226
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
  • medium Excessive Agency · line 413
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 417
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 452
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 456
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 464
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 1000
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
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 $0.00073 $0.16394
Opus 5 $0.00036 $0.08197
Sonnet 5 $0.00015 $0.03279
Haiku 4.5 $0.00007 $0.01639

Measured 8d ago against content hash 6ef545568d31, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

roundtrip-radar 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 8d 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.

skills/roundtrip-radar/SKILL.md · 1,170 lines

How it starts

The opening of the file, as written. The whole thing — 1,170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Roundtrip Radar

This skill audits application workflows for bugs, data-safety issues, performance problems, and data round-trip completeness. It operates in three primary steps plus two targeted entry points:

  • Step 0 — Discover all workflows (run once, or when workflows change)
  • Step 1 — Deep audit one workflow at a time (one prompt per workflow)
  • Step 2 — Roll-up cross-cutting patterns across all audited workflows
  • Trace — Audit a specific user journey described in natural language (see § Trace Command)
  • Diff — Compare findings against the previous audit's ledger entries (see § Diff Command)

Usage

Command Description
/roundtrip-radar Start with Step 0 (discover), then prompt for Step 1
/roundtrip-radar discover Run Step 0 only — find all workflows
/roundtrip-radar [WORKFLOW] Run Step 1 for a specific workflow
/roundtrip-radar rollup Run Step 2 — cross-cutting analysis
/roundtrip-radar trace "A → B → C" Trace a specific user flow path (see below)
/roundtrip-radar diff Compare findings against previous audit
--show-suppressed Show findings suppressed by known-intentional entries
--accept-intentional Mark current finding as known-intentional (not a bug)

Trace Command

Targeted flow tracing — trace a specific user journey described in natural language.

Usage

/roundtrip-radar trace "Dashboard → Add Item → Photo → Save"
/roundtrip-radar trace "Settings, Export, CSV, Email"

How It Works

  1. Parse the path — Split on , ->, or , into discrete steps
  2. Identify code locations — For each step, search for:
    • View names matching the step
    • Sheet triggers, navigation actions
    • Button labels, action handlers
  3. Trace step by step — For each transition:
    • File and line number
    • State changes (sheet presentations, navigation, @State mutations)
    • Data transformations (what model fields are read/written)
  4. Check for issues at each step:
    • Is data preserved between steps? (Round-trip completeness)
    • Are collections preserved or silently narrowed? (Collection narrowing)
    • Are there error paths that lose context? (Error handling)
    • Is the user's intent preserved? (Data safety)
    • Are there race conditions? (Concurrency)
  5. Output — Issue Rating Table for findings + step-by-step trace with receipts

Read the full file on GitHub · 1,170 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 1,170 lines · 73 tokens per session scan A 6ef545568d31

Subscribe to this mod's changes

roundtrip-radar is a skill published in the GitHub repository Terryc21/radar-suite (20 stars, last pushed 10d ago), licensed Apache-2.0. It adds 73 tokens to every session and 16,394 once invoked, about $0.0004 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.

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