A command for analyzing a brand or topic using the sources tracked in a project. It first defines which sources are included, so reported results have a clear scope.

Selecting or creating a project, narrowing its source list, checking available labels, and gathering data for the requested analysis.

It prevents an analysis from quietly using the wrong collection of sources or treating unavailable data as complete.

analyze — Command for Claude Code by adologyai

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/adologyai/content-intelligence-plugin

Made for: Claude Code.

Or install content-intelligence, the plugin that ships this one along with the rest of its 14 skills, 4 commands, 1 agent.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/adologyai/content-intelligence-plugin/analyze/github.svg)](https://agentmods.dev/commands/adologyai/content-intelligence-plugin/analyze)

Your own site

<a href="https://agentmods.dev/commands/adologyai/content-intelligence-plugin/analyze"><img src="https://agentmods.dev/badge/commands/adologyai/content-intelligence-plugin/analyze/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/adologyai/content-intelligence-plugin/analyze"><img src="https://agentmods.dev/badge/commands/adologyai/content-intelligence-plugin/analyze.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,292 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.

Model	Per session	Once invoked
Fable 5.1	$0.00013	$0.01292
Opus 5.5	$0.00005	$0.00517
Sonnet 5.5	$0.00003	$0.00258
Haiku 4.5	$0.00001	$0.00129

Measured 2mo ago against content hash a7670ccecbc5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

analyze 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 2mo 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.

commands/analyze.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When the user invokes /analyze, follow this process:

1. Land in a scope

A read is only as good as what it is about. Orient with whoami, then list_portfolios, then list_projects({ portfolioId }). Reuse a project that already covers the subject, or create_project for a fresh one — there is no special home project.

Call get_project before analyzing. It returns the project's dataScope (the tracked set of sources it reads) plus per-source access: expiredSources have data only through a date, ungrantedSources are tracked but not yet acquired. That list is the denominator behind every number you are about to report. A project with an empty scope reads the portfolio's whole tracked universe until it is narrowed.

To point the project at exactly the sources this question is about, use update_project_scope: add extends, remove trims, replace pins the scope to exactly the sources you name. Adding sources the pool already covers is free and instant.

2. See which dimensions exist

Call list_labels({ projectId }) for the label dimensions and top values actually present in this scope. Use those exact names in labelFilter and get_table_data rows — a dimension the scope does not carry matches nothing, so an invented name turns the whole read into an empty result. If list_labels reports nothing, the scope holds no labeled items yet: analyze on engagement and content instead, and say that labels are unavailable.

3. Read what is already there

analyze({ projectId, query }) is the workhorse. It returns posts with their creative analysis — hookMechanism, creativeConcept, adDescription, transcript, oneLineInsight — from the resolved scope. Choose the retrieval that matches the question:

distribution: "balanced" (default) for a representative read across sources.
distribution: "top" (with sortMetric) for the highest-engagement content per source.
distribution: "exhaustive" with sortBy: "likesMultiple" (or another *Multiple) for a real ranked leaderboard over the full filtered set, with totalEstimated and nextOffset for paging.
mode: "semantic" when the ask is a meaning ("posts that make sustainability feel effortless") rather than a filter.

Read the full file on GitHub · 63 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.

2mo ago First seen · 63 lines · 13 tokens per session scan A a7670ccecbc5

Subscribe to this mod's changes

analyze is a command published in the GitHub repository adologyai/content-intelligence-plugin (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 13 tokens to every session and 1,292 once invoked, about $0.0001 per session on Opus 5.5. 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.

Marketing and SEO Research

analyze next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
analyzeadologyai/content-intelligence-plugin	Command	2	1mo ago	Apache-2.0	A	13	Claude Code
checklistgithub/spec-kit	Command	148k	today	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	today	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	today	MIT	A	13	Claude Code
convergegithub/spec-kit	Command	148k	today	MIT	A	35	Claude Code
speckit.bug.testgithub/spec-kit	Command	148k	today	MIT	A	13	Claude Code
analyzegithub/spec-kit	Command	148k	today	MIT	A	26	Claude Code