> ## Documentation Index > Fetch the complete documentation index at: https://docs.aigrowthagent.co/llms.txt > Use this file to discover all available pages before exploring further. # Prompts and resources > Guided workflows and reference documents the server ships alongside its tools — how to invoke them, when to use each, and how to mirror them as client-side skills. Beyond tools, the server ships two kinds of guidance: **prompts** and **resources**. Both encode the opinionated workflows behind the tools, so a client that has never seen the data still runs the analysis the way an expert would. ## What prompts are A prompt is a pre-written instruction message the server hands to your client when you invoke it. Invoking a prompt injects an expert checklist into the conversation — the tool sequence to run, the watchouts to apply, and the order that matters — and your client then executes it with the tools. Prompts take no arguments; they act on the session's current account (or whatever `accountId` you pass). ## What resources are A resource is a markdown document the server serves at an `aga://` URI. Your client can read one mid-task — the way it would read a file — to load the long version of a rule set without leaving the session. The three resources are the operational condensation of this site's guides. ## How to invoke them * **Claude Code** — server prompts appear in the `/` slash menu; pick one to run it. Resources can be read by their URI. * **Cursor and Claude Cowork** — prompts appear in the client's UI for the connected server; invoke them from there. * **Any agent** — you can also just tell it: "use the `content-deep-dive` prompt on this account." The client fetches the prompt message and follows it. Fallback: everything the prompts and resources say is mirrored in these guides. If your client cannot invoke prompts or read resources, paste the relevant guide into the conversation — same content, same result. ## The prompts Five pairs plus `wins-digest`. In each pair, the general prompt crosses data from all the tools — it dispatches one subagent per data section (universe, citations and mentions, content, GSC) and synthesizes the briefs — while the `gsc-` variant runs the Google Search Console-only path. | Prompt | Use it when | | ----------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `explore` | You are on an account you have never touched. Orients across the whole system before any performance question: publishing setup, the search universe, citations and mentions, and a first GSC overview | | `gsc-explore` | You only need the GSC orientation: `gsc_get_context` first (reverse-proxy rewrites, property set, maturity cadence, placeholder flag), then `gsc_list_sites`, then `gsc_get_overview` read impressions-first | | `performance-check` | You want the periodic "how is the account doing" read across the full loop: search universe, citations and mentions, published content, and GSC movement, crossed together | | `gsc-performance-check` | You only need the GSC read. Picks the cadence from account maturity (week-over-week only in the first \~8 weeks), runs `gsc_compare_periods`, and separates the impression growth share (AI visibility) from the click share (human traffic) | | `wins-digest` | You want "what did we win this week" on Google. Snapshot dates from `reporting_get_available_dates`, then `reporting_get_wins`, then planner drill-down. Google-only — never mixes in ChatGPT modes | | `content-deep-dive` | You are mapping the account's full system: search universe, published corpus, citations and mentions per term, and GSC performance per page — crossed together | | `gsc-content-deep-dive` | You are running the GSC-only deep analysis. The complete runbook: site structure before cohorts, quota budgeting, monthly exports under the 25k cap, the anonymization block before any query-level claim | | `page-diagnosis` | You want one page's full footprint: what it earns in Google search and where it is cited or mentioned across the universe, ending in a keep / refresh / retire / replicate call | | `gsc-page-diagnosis` | You only need the GSC page read. What queries the page earns — including demand beyond the query it was published for, its blast radius — then `gsc_get_page_performance` → `gsc_inspect_url` (with the canonical-URL caveats) → `gsc_list_sitemaps` | | `trend-explanation` | A number moved — a citations/mentions rate or a GSC metric — and you need to know why: universe-size change, recent publishes, dilution vs decay, net vs gross churn | | `gsc-trend-explanation` | A GSC number moved. `gsc_compare_periods` movers plus the AGA split, dilution vs decay, net vs gross churn, and the universe-size check before any rate read | ## The three resources | Resource | Read it when | | ---------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `aga://guides/first-analysis` | Before running a deep analysis on a new account — the Phase 0–5 runbook as a checklist | | `aga://guides/gsc-data-fidelity` | Before trusting any figure from the `gsc_*` tools — what the instrument does to the data (anonymization, lag, row caps, quota, remote files) | | `aga://guides/analysis-guardrails` | Before modelling anything from search data — the analytical patterns that keep the analysis honest (de-trending, balanced panels, placebos, dilution vs decay) | ## Client-side skills Prompts and resources live on the server. If your agent harness supports installable skills (a `SKILL.md` with a `name` and `description`), you can also install small wrappers that trigger the same workflows from your own side. A skill description should state only the triggering conditions — start it with "Use when…" — and the body should stay a short checklist that points at the guides rather than duplicating them. Two examples: ```markdown theme={null} --- name: aga-gsc-weekly-check description: Use when asked for a periodic account check-in, a weekly performance read, or a wins digest on an AI Growth Agent account. --- - Invoke the `performance-check` prompt (or follow https://docs.aigrowthagent.co/guides/prompts-and-resources). Cadence comes from account maturity: week-over-week only in the first ~8 weeks of publishing, month- or quarter-over-quarter after. - Invoke the `wins-digest` prompt for the week's new citations and brand mentions. Google-only — never mix in ChatGPT modes. - Read impressions first: impression growth share is the AI-visibility read; the click share is human traffic. Never present a click move as an AI-visibility move. - Read every rate change against universe size: a dip against a growing universe is expansion, not decline. ``` ```markdown theme={null} --- name: aga-gsc-deep-analysis description: Use when asked to run a full content-performance analysis, an audit, or any modelling work over Google Search Console data on an AI Growth Agent account. --- - Invoke the `gsc-content-deep-dive` prompt and follow https://docs.aigrowthagent.co/guides/first-analysis phase by phase: site structure before cohorts, budgeted acquisition, panel construction, ground truth — then model. - Pull `[page, query]` early and read `meta.anonymization` before any query-level claim — named queries are a biased floor (https://docs.aigrowthagent.co/guides/gsc-data-fidelity). - `curl` every export `downloadUrl` immediately — files are remote and the signature expires in ~1 hour. - Before modelling, apply the guardrails: de-trend every age curve, use balanced panels, run placebos before believing any event study, and separate dilution from decay (https://docs.aigrowthagent.co/guides/analysis-guardrails). ``` Install either file under your harness's skills directory and it triggers on the matching requests. Keep them thin — when the workflows evolve, the server prompts and these guides are the source of truth, not the skill body. ## See also * [First analysis on an account](/guides/first-analysis) — the Phase 0–5 runbook the `gsc-explore` and `gsc-content-deep-dive` prompts follow * [GSC data fidelity](/guides/gsc-data-fidelity) — the instrument watchouts behind `aga://guides/gsc-data-fidelity` * [Analysis guardrails](/guides/analysis-guardrails) — the patterns behind `aga://guides/analysis-guardrails` * [Common workflows](/workflows) — the tool-level recipes the prompts wrap