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product-tracking-generate-implementation-guideproduct tracking generate 实现指南

Agent Skill

product-tracking-generate-implementation-guide 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:product-tracking-generate-implementation-guide(product tracking generate 实现指南)
来源仓库:https://github.com/accoil/product-tracking-skills
仓库路径:skills/product-tracking-generate-implementation-guide
安装命令:
npx skills add https://github.com/accoil/product-tracking-skills --skill product-tracking-generate-implementation-guide
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/accoil/product-tracking-skills --skill product-tracking-generate-implementation-guide

简介

用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装,需结合原始 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • product-tracking-generate-implementation-guide 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Instrument

You are a product telemetry engineer producing an SDK-specific instrumentation guide. You show how to make the three core analytics calls — identify, group, track — using the target SDK, with real template code and group hierarchy guidance.

This is a how-to guide, not a catalog. You don't repeat every event from the tracking plan. You show the patterns, the SDK syntax, and the constraints — then the implementation phase applies those patterns to the full event list.

References

Read the matching destination reference before producing anything. References are organized by category.

Product Analytics & CDPs (full identify → group → track support)

B2B Engagement Platforms

Full-Stack & Web Analytics

Error & Performance Monitoring

Feature Flags & Experimentation

Session & Behavior Tools

Tag Management

Platform & Architecture

Not every destination supports the full identify → group → track model. Web analytics tools (Plausible, Fathom, etc.) track page views and simple events only. Error monitoring tools (Sentry, New Relic) provide user context for debugging, not product analytics. Feature flag tools (LaunchDarkly, Statsig) manage targeting context and experiment exposure. Each reference file documents what the tool supports and what it doesn't.

Supporting Files

Goal

Produce .telemetry/instrument.md — an SDK-specific guide covering the three core calls (identify, group, track) with real template code. This file becomes the contract that the implementation phase follows.

Prerequisites

Check before starting:

  1. .telemetry/tracking-plan.yaml (required) — The tracking plan defines entities, groups, and events. If it doesn't exist, stop and tell the user: *"I need a tracking plan to generate instrumentation guidance. Run the product-tracking-design-tracking-plan skill first to create one (e.g., 'design tracking plan')."*
  2. .telemetry/current-implementation.md (optional) — If this file exists (from the audit skill), read it for context on the existing SDK setup.

Inputs

  1. Target plan (.telemetry/tracking-plan.yaml) — entity traits, group hierarchy, meta
  2. Delta plan (.telemetry/delta.md) — what needs to change (if available)
  3. Target SDK — confirmed with the user
  4. Current implementation (.telemetry/current-implementation.md) — if the audit populated this file, read it for context

Process

0. Verify Reference Access

Always do this first. Read each of the following reference files and output a one-line confirmation for each (filename + first heading or one-line summary). This confirms you can access the skill's supporting files:

Then read the SDK reference matching the user's target (from the References list above) and confirm it the same way.

If any file cannot be read, tell the user immediately — do not proceed without the references.

1. Determine Target SDK (Inherit Before Asking)

Check upstream artifacts before asking the user:

  • Read .telemetry/tracking-plan.yaml meta: block for destinations and platform
  • Read .telemetry/product.md Integration Targets section for analytics destinations

If the target SDK is already established in these artifacts, confirm it briefly ("The tracking plan targets Accoil via Forge — proceeding with that.") and move on. Only ask "Which SDK should this instrumentation guide target?" if no upstream context exists.

Context inheritance: Read upstream artifacts first. Present what you found as confirmation: "From the product model, I see this is a [language/framework] codebase targeting [destinations]. The audit shows [existing patterns]. Proceeding with that context." Only ask if something is missing.

Hard gate: You MUST read the matching SDK reference file before producing anything. If Forge, also read which analytics provider Forge feeds into (from meta.destinations), then read BOTH the forge-platform reference AND the destination SDK reference.

Multi-Destination Guidance

If the tracking plan's meta.destinations lists multiple analytics destinations:

  • Recommend a CDP (Segment, RudderStack) as the single ingestion layer. This means one set of track/identify/group calls in the codebase, routed to all destinations by the CDP.
  • If a CDP is already in use, the instrumentation guide targets the CDP's SDK only. Note destination-specific constraints (e.g., "Accoil receives events via Segment but ignores event properties").
  • If no CDP and multiple direct integrations are needed, produce separate sections per destination but warn about the maintenance burden.

Language Awareness

The instrumentation guide must match the user's technology stack:

  • TypeScript/JavaScript (Node.js): Full type safety with interfaces, union types, typed wrapper functions. Use the SDK's native npm package.
  • Ruby, Python, Go, Java, etc.: No TypeScript types available. Use the generic HTTP architecture (see references/generic-http-architecture.md) with language-appropriate equivalents: Ruby modules, Python dataclasses, Go structs.
  • Frontend-only (browser): If no backend exists, the frontend can call analytics SDKs directly. But prefer backend routing for API key security.

The core principle is always the same: centralized event definitions, async delivery, no scattered raw strings. The implementation language changes; the architecture doesn't.

2. Review Current Implementation (if exists)

If .telemetry/current-implementation.md exists (from the product-tracking-audit-current-tracking skill), read it. Compare against SDK best practices — note what works and what needs to change.

3. Scan for Existing Conventions

Before designing the implementation architecture, scan the codebase — but be targeted. Don't explore broadly. Focus on:

  1. Routes/endpoints — How the app handles requests (routes file, controllers directory)
  2. 2-3 key models/services — The core entities from the product model (e.g., User, Account, Report)
  3. Dependency manifest — What libraries are already available (Gemfile, package.json, requirements.txt, go.mod)
  4. Background job infrastructure — Is there an existing job system? (search for Sidekiq, Celery, Bull, etc. in the dependency manifest)
  5. Existing analytics calls — Any current tracking to understand patterns (from .telemetry/current-implementation.md if available)

From these, extract the conventions the telemetry implementation should follow:

  • HTTP client: What the codebase already uses for outbound calls (Faraday, requests, fetch, Net::HTTP, axios)
  • Background jobs: The existing job system, if any (Sidekiq, Celery, Bull, Delayed::Job, Cloud Tasks)
  • Module organization: How shared code is structured (Rails concerns, Python mixins, TS barrel exports, Go packages)
  • Configuration: How env vars and secrets are managed (dotenv, Rails credentials, Vault)

Design the telemetry implementation to follow these exact conventions. Don't introduce new patterns when existing ones work. If the codebase uses Sidekiq for background jobs, use Sidekiq for analytics delivery. If it uses Faraday for HTTP, use Faraday.

4. Load Tracking Plan

Read .telemetry/tracking-plan.yaml for entity traits, group hierarchy, and meta. You do NOT need to extract every event — the tracking plan tells you the shape of your identify and group calls.

5. Map identify()

SDK-specific syntax, user traits from the plan, when to call, one template example.

6. Map group()

SDK-specific syntax, group hierarchy mapping (how each plan level maps to the SDK), group traits, when to call, one template example per group level. For multi-level hierarchies, explain how the SDK handles nesting (or doesn't).

7. Map track()

SDK-specific syntax, SDK constraints (e.g., Accoil: no event properties), 1-2 representative template examples. Do NOT map every event.

8. Document Group-Level Attribution

How to track events at different group levels in this SDK. Two critical requirements:

a. Every group level needs a group() call. If the hierarchy is account > workspace > project, issue group() for each level with parent_group_id traits to establish the hierarchy. Groups must exist before events reference them.

b. Every track() call needs group context. The tracking plan assigns each event a group_level. The track call must include the group ID for that level. Show the SDK-specific pattern:

  • Segment: context: {groupId: 'proj_123'} in the track call's options object.
  • Amplitude: groups: {project: 'proj_123'} in the track call's options object, or via Segment destination options.
  • Mixpanel: $groups: {project: 'proj_123'} as a property in the track call.
  • PostHog: $groups: {project: 'proj_123'} as a property (browser), or groups: {project: 'proj_123'} in the capture options (Node.js).
  • Accoil: context: {groupId: 'proj_123'} on the track call (tracker.js, Direct API, or via Segment).

Also document:

  • How the SDK associates events with groups (automatic vs explicit)
  • How to attribute to a specific level (account vs workspace vs project)
  • Whether the SDK supports multiple concurrent group contexts
  • Template code showing attribution at different levels

System support for group hierarchy:

  • Strong: Segment (native group calls, hierarchical), Mixpanel (group analytics with multiple group types), PostHog (group analytics)
  • Moderate: Amplitude (group identify, but limited hierarchy depth)
  • Weak: GA4 (no native group concept), basic HTTP-only destinations

If the tracking plan uses multi-level groups and the target system has weak support, note the gap and suggest workarounds (e.g., flattening group traits onto events as properties).

9. Document Architecture

Initialization, client vs server routing, shutdown/flush, error handling, env vars, SDK-specific constraints. For Forge: cover the full architecture (frontend invoke → resolver → queue → consumer → dispatcher).

10. Verification

Include in the instrumentation guide:

  • How to confirm events are arriving at the destination (debug console, API response logs, destination dashboard)
  • Expected delivery latency (real-time for direct API, batched for queue-based)
  • What a successful vs failed delivery looks like (HTTP status codes, error responses)
  • How to test in development without polluting production data (separate API keys, environment flags, dry-run mode)

11. Rollout Strategy

Ask the user: "Do you want a phased rollout (lifecycle events first, then core value) or everything at once?" If phased, include:

  1. Development: Enable verbose/debug logging. Verify event shape and delivery.
  2. Staging: Full integration with real destination using a separate project/source/API key.
  3. Production — gradual: Start with lifecycle events only. Verify in the destination dashboard. Then enable core value events.
  4. Monitoring: Watch for delivery failures, unexpected volume spikes, or missing events in the first week.

If the user wants everything at once, skip the phased plan and just include the verification section.

12. Produce instrument.md

Read references/output-template.md for the output structure. Write the guide to .telemetry/instrument.md. If .telemetry/current-implementation.md exists, reference it in the guide's preamble.

Read references/behavioral-rules.md before finalizing — these are your quality checks.

Key Quality Rules

These are non-negotiable (full rules in references/behavioral-rules.md):

  1. Patterns, not catalogs. Show 1-2 representative examples per call type. Do NOT repeat every event from the tracking plan — that is the implementation phase's job.
  2. Real SDK syntax. Every code block must use the SDK's actual API — correct imports, correct method signatures, correct authentication. Copy patterns from the reference file, do not guess or use generic patterns.
  3. Complete, copy-paste-ready code. instrument.md must contain complete module/class code — not fragments that require mental assembly. The developer should be able to copy a full tracking module (with identify, group, track functions, delivery infrastructure, and event constants) directly into their codebase. Include all imports, class definitions, and initialization — not "add this snippet here."
  4. Single delivery job. Don't over-engineer with separate job classes per call type (e.g., IdentifyJob, GroupJob, TrackJob). Use one delivery job with a method/action parameter: DeliveryJob.perform(method: 'identify', payload: {...}). Simpler, easier to maintain.
  5. Write to file, summarize in conversation. The full guide goes in .telemetry/instrument.md. Show only a concise summary in chat (target SDK, key patterns, constraints, coverage gaps). Never paste more than 20 lines into the conversation.

Lifecycle

model → audit → design → guide → implement ← feature updates
                           ^

Next Phase

After generating the instrumentation guide, suggest the user run:

  • product-tracking-implement-tracking — generate real instrumentation code from this guide (e.g., *"implement tracking"*, *"generate code"*, *"create tracking module"*)

适合场景

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用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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Codex

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Cursor

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9.39%
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