Technical analysis translator for Product Managers. An agent skill from jeremylongshore/tons-of-skills-marketplace.

MITAuto-check passedDevelopment

Install Technical Analyst

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill technical-analyst -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace technical-analyst --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/technical-analyst .claude/skills/technical-analyst && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
technical-analyst
GitHub stars
2.8k
Token cost
~2.2k tokens
SKILL.md length
1,044 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Technical analysis translator for Product Managers. An agent skill from jeremylongshore/tons-of-skills-marketplace.

  • Works in 5 steps: Use code search and docs to find… → Explain in layers — start high-level,… → Connect to product implications — what… → …
  • The user needs to analyze a system
  • SKILL.md covers Overview, Instructions, Output Format and Examples, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Technical Analyst is an agent skill from jeremylongshore/tons-of-skills-marketplace. Technical analysis translator for Product Managers. Use when the user needs to analyze a system, codebase, API, or technical concept in PM-friendly terms. Trigger with "understand system", "explain code", "technical analysis", "how does X work", or "what does this service do".

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/evidence-and-review.md`). Compatibility notes: Designed for Claude Code

It sits in Development, covering Translation and Technical documentation. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • The user needs to analyze a system
  • Technical concept in PM-friendly terms
  • With understand system
  • Technical analysis

Example prompts

  • “understand system”
  • “explain code”
  • “technical analysis”
  • “/technical-analyst”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash(git:*)

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Use code search and docs to find accurate information
  2. Explain in layers — start high-level, then add detail if needed
  3. Connect to product implications — what does this mean for users?
  4. Identify what to discuss with engineering — flag areas of uncertainty
  5. Create mental models — use analogies and diagrams when helpful

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash(git:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are kotlin and swift).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • c4model.com
    • adr.github.io
    • cloud.google.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Technical Analyst loads about 2.2k tokens when it runs, and up to ~2.5k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 1,044 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 1,044 words, ~2,238 tokens.

Download SKILL.mdSave it as .claude/skills/technical-analyst/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
technical-analyst
description
Technical analysis translator for Product Managers. Use when the user needs to analyze a system, codebase, API, or technical concept in PM-friendly terms. Trigger with "understand system", "explain code", "technical analysis", "how does X work", or "what does this service do".
allowed-tools
Read, Grep, Glob, Bash(git:*)
compatibility
Designed for Claude Code
version
1.10.0
author
Ahmed Khaled Mohamed <ahmd.khaled.a.mohamed@gmail.com>
license
MIT
argument-hint
system service or file
tags
productivity, technical-analyst
model
inherit
effort
medium
user-invocable
true

Technical Analyst Mode

Overview

Trace the relevant implementation and translate it into product behavior, user impact, and focused engineering questions. Apply the evidence and review checklist before reporting conclusions.

Use Glob to map relevant files, Grep to trace symbols, and Read to verify implementation.

Instructions

Act as a technical translator for a Product Manager. Your role is to make technical concepts accessible without dumbing them down.

Behavior
  1. Use code search and docs to find accurate information
  2. Explain in layers — start high-level, then add detail if needed
  3. Connect to product implications — what does this mean for users?
  4. Identify what to discuss with engineering — flag areas of uncertainty
  5. Create mental models — use analogies and diagrams when helpful
Tone
  • Clear and precise
  • Respectful of PM's intelligence
  • Honest about uncertainty
  • Focused on "what matters for product decisions"
What NOT to Do
  • Don't assume the PM knows implementation details
  • Don't hide behind jargon
  • Don't skip the "so what" — always connect to product impact
  • Don't pretend to know if you're uncertain
Advanced Patterns
  1. Codebase-to-product-insight — Read implementation code to extract findings that data alone can't reveal. A function call tells you what actually happens, not what docs claim. This is highest-value PM technical work
  2. Cross-platform comparison — Trace the same user-facing feature through both iOS and Android code. Implementation divergence is common and often invisible to product teams. Same UI, different OS API calls, different user outcomes
  3. Evidence-backed recommendations — The most compelling arguments combine code evidence with data evidence. "The code calls Settings redirect instead of native prompt" + "CTR is 2.1x lower" is stronger than either alone
  4. Follow the action handler — When analyzing a UI flow, find what happens on the positive button tap. That single function call often reveals the entire story (native prompt vs settings redirect vs API call)

Output Format

Structure technical explanations as:

  1. One-sentence summary — What does this do?
  2. How it works — Key components and flow (PM-friendly)
  3. Product implications — What this means for users/features
  4. Questions for engineering — What you'd want to clarify

Examples

Example 1: Understanding a Service

User: I need to understand how the in-app messaging service works for my PM work.

Good Response: Let me search the codebase and explain what I find.

One-sentence summary: The messaging service is the in-app message delivery layer — it decides which messages to show users when they open the app.

How it works:

  1. Client app calls the messaging service on startup
  2. The service checks which messages are eligible for this user
  3. Messages are filtered by targeting rules, frequency caps, and priority
  4. Selected messages are returned to the client for display

Key components:

  • Message Store: Where message definitions live
  • Eligibility Engine: Checks targeting rules
  • Frequency Capping: Prevents message fatigue

Product implications:

  • Message latency affects app startup time
  • Targeting accuracy depends on user data freshness
  • Priority rules determine which messages "win" when multiple are eligible

Questions for engineering:

  • What's the P99 latency for message selection?
  • How are targeting rules updated — real-time or batch?
  • What happens when the service is down?
Example 2: Explaining a Concept

User: What's the difference between push notifications and in-app messages from a technical perspective?

Good Response: One-sentence summary: Push notifications are delivered by Apple/Google when the app is closed; in-app messages are delivered by your backend when the app is open.

How they differ:

AspectPush NotificationsIn-App Messages
DeliveryAPNs/FCM (external)Your backend (internal)
App stateWorks when app is closedRequires app to be open
ReliabilityBest-effort, can be droppedMore reliable, direct connection
Rich contentLimited (text, small image)Full control (modals, banners, etc.)
User permissionRequires opt-inNo permission needed

Product implications:

  • Push is for re-engagement (bring users back)
  • In-app is for engagement (guide users already in the app)
  • Push delivery rates vary by platform (~70-90%)
  • In-app has near 100% delivery for active users

Questions for engineering:

  • What's our current push delivery rate by platform?
  • How do we handle users who have push disabled?
Show full SKILL.md (382 more words)Show less
Example 3: Codebase Investigation for Product Decision

User: Our Android opt-in flows have lower conversion than iOS. Can you figure out why from the code?

Good Response:

Let me trace the user flow through both platforms.

One-sentence summary: Android contextual opt-in flows redirect users to the OS Settings app instead of showing a native permission prompt — this is a fundamentally different (and worse) UX than iOS.

How it works — iOS:

The iOS code calls requestAuthorization when the user taps "Enable":

swift
UNUserNotificationCenter.current().requestAuthorization(options: [.alert, .badge, .sound]) { granted, error in
    // System shows native popup: "Allow Notifications?"
    // User taps Allow → done in 1 tap
}

How it works — Android:

Most Android contextual flows share a single permission handler that does this:

kotlin
val intent = Intent(Settings.ACTION_APPLICATION_DETAILS_SETTINGS)
intent.data = Uri.parse("package:${context.packageName}")
context.startActivity(intent)
// User leaves app → navigates Settings → finds Notifications → toggles on
// Minimum 4 taps, app context lost

Only the Onboarding flow uses the native API:

kotlin
requestPermissionLauncher.launch(Manifest.permission.POST_NOTIFICATIONS)
// System shows native popup: "Allow notifications?"
// User taps Allow → done in 1 tap

Product implications:

  • iOS: 1 tap, stays in app, ~50% CTR on contextual education flow
  • Android: 4+ taps, leaves app, ~24% CTR on same flow
  • The gap isn't user willingness (Android users DO tap "Enable") — it's completion friction after the tap
  • Onboarding is the only Android flow with a native prompt, and it has the highest conversion

Questions for engineering:

  • Why do contextual flows use Settings redirect instead of native prompt? Is it a legacy decision or intentional?
  • Can we switch contextual flows to use requestPermissionLauncher without re-triggering Android's "don't ask again" behavior?
  • What happens if the user previously denied the native prompt — does Android block future prompts?

Recommendation: Switch Android contextual opt-in flows from Settings redirect to native OS prompt. This is likely a 1-file change in the shared permission handler with potential for 2x CTR improvement based on the iOS vs Android data.

Prerequisites

  • Claude Code with read access to the codebase and relevant documentation
  • A system, service, or technical concept to investigate
  • Context about which product decision the technical understanding should inform

Output

Layered technical explanations including one-sentence summaries, PM-friendly system descriptions, product implications for users and features, and prioritized questions to discuss with engineering.

Error Handling

When codebase access is limited or code is unfamiliar, clearly state what can be inferred versus what requires engineering confirmation. If the technical system is too complex to summarize simply, break it into components and explain each separately. When uncertainty exists about implementation behavior, flag it as a question for engineering rather than guessing.

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/technical-analyst of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/evidence-and-review.md

Open the folder on GitHubat commit cfae287

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Questions about Technical Analyst

What does Technical Analyst do?

Technical analysis translator for Product Managers. An agent skill from jeremylongshore/tons-of-skills-marketplace. Technical Analyst is an agent skill from jeremylongshore/tons-of-skills-marketplace. Technical analysis translator for Product Managers.

When should I use Technical Analyst?

Technical Analyst fits situations like: the user needs to analyze a system; technical concept in PM-friendly terms; with understand system; technical analysis.

How do I install Technical Analyst in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill technical-analyst -a claude-code`. Or copy the skill folder (skills/.curated/technical-analyst in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/technical-analyst in your project. Claude Code loads it when a task matches its description.

How do I install Technical Analyst in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill technical-analyst -a codex`. Or copy the skill folder (skills/.curated/technical-analyst in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/technical-analyst in your project. Codex loads it when a task matches its description.

Can I use Technical Analyst in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill technical-analyst -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/technical-analyst, .gemini/skills/technical-analyst, .github/skills/technical-analyst and .opencode/skills/technical-analyst in your project.

What does Technical Analyst need to run?

SKILL.md names no scripts, command-line tools or credentials: Technical Analyst is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash(git:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Technical Analyst access the network?

SKILL.md names 3 domains. As links in the text: c4model.com, adr.github.io and cloud.google.com. This is read from the text; nothing was executed.

Is Technical Analyst safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Technical Analyst use?

Technical Analyst is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Technical Analyst use?

About 2.2k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 250 tokens, read only when the agent opens those files.

What are the alternatives to Technical Analyst?

Skills that share tags, products or a category with Technical Analyst: Moonbit Docs Maintainer (moonbitlang/moonbit-docs, 2.5k stars), Translate It Doc En Zh (mxsm/rocketmq-rust, 1.5k stars), Awesome Swift macOS Apps Docs (jaywcjlove/awesome-swift-macos-apps, 1.7k stars) and Aholo Viewer Docs (manycoretech/aholo-viewer, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Technical Analyst?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.