End-to-end: Competitive research report

This is a complete flow you can copy verbatim. When you finish, you’ll have a 10-20 page competitive research document (.docx or .pdf) where every claim traces back to a source link, and where the total cost was predictable before you started. This scenario opens the guides because it stacks the three things people most often misjudge about Profy: search spends money on reading results, not on issuing queries; nothing counts as delivered until it lands in a file; and research without citations is not research. All three generalize to any information task, so getting burned once here saves you everywhere else.

What you’ll get

Artifact	Location	Notes
Research document	Workspace `research/competitor-report.docx`	Structured sections, comparison tables, source footnotes
Raw findings	Workspace `research/sources/*.md`	One file per source, easy to re-check and reuse
Comparison matrices	Embedded tables (exportable to `.xlsx`)	Features, pricing, positioning

Prerequisites

Confirm the sandbox is available

Research writes files, so a sandbox is required. It starts automatically the first time the agent writes a file in a new session — just confirm you can see the file tree in the workspace panel. Experts configured with no sandbox cannot do this.

Confirm you have enough credits

Work out the expected spend from the cost section below and keep at least 2× that in your balance. Running out mid-flow interrupts the run; whatever was already written to files survives, but you’ll have to restart the remaining steps.

Prepare the competitor list yourself

Write down 3-8 competitors and their domains up front. Asking the agent to “also find all the competitors” makes the number of searches unbounded and tends to drag in irrelevant companies.

Steps

Step 1: Fix the framework before searching

“Research A, B and C for me” produces a pile without a skeleton. Nail down the evaluation dimensions first:

I need competitive research on Notion, Coda, and Airtable.
It feeds an internal product decision; the focus is how each prices team collaboration.

Don't search yet. First give me a research framework:
1) Which dimensions you'll compare on (six at most)
2) What kind of source you'll use for each dimension
   (official site / pricing page / third-party review / user community)
3) Which dimensions you expect to find no public data for

I'll confirm the framework before you start searching.

Asking which dimensions have no public data is the highest-value part of this step. It surfaces metrics like customer retention or actual ARR — things you cannot get from public sources — before they end up as invented numbers in a table.

Step 2: Search one dimension at a time and write to disk

Once the framework is agreed, work dimension by dimension and write a file after each one:

Framework confirmed. Work through the dimensions one at a time.
After each dimension, do two things:

1. Write raw findings to research/sources/<dimension>.md, formatted as:
   claim + verbatim quote + source URL + retrieval date
2. Tell me your confidence in that dimension (high/medium/low) and why

Start with "Pricing and plan structure", then stop and wait for me.

One dimension at a time is deliberate. Firing many searches in parallel pulls all the result bodies into context at once, which can exhaust the conversation budget before you’ve seen a single artifact.

Step 3: Handle what can’t be reached

Search only reaches publicly crawlable content. Pricing pages often render via JavaScript or hide behind a login, so switch tools:

The Coda team pricing page came back empty.
Open https://coda.io/pricing in the browser, take a screenshot,
and read the actual prices off the screenshot.
If the page requires a login, say so — don't guess.

The sandbox browser has none of your logins. “Content behind a login” is therefore a hard boundary — the right outcome is the agent stating it can’t reach it, and you supplying a screenshot yourself.

Step 4: Cross-check and surface contradictions

All three dimensions are done. Now cross-check:

1. List every data point where sources contradict each other,
   with both sides and their sources
2. For each contradiction, give your judgment on which is more credible and why
3. Do NOT smooth contradictions into a compromise number

Write the list to research/sources/_conflicts.md.

Don’t skip this. Competitor pricing varies by region, source, and date, and the default tendency is to settle on a plausible-looking middle value — a number that matches nothing. Keeping contradictions explicit is what tells readers which conclusions still need verifying.

Step 5: Produce the document

Now generate the document: research/competitor-report.docx

Requirements:
- Structure: summary / three matrices (features, pricing, positioning) /
  per-company detail / contradictions and open questions / recommendations
- Footnote every data point, pointing at the specific source URL in research/sources/
- Keep the "contradictions and open questions" section — don't drop it
  because it makes the conclusion look less clean
- Use real tables, not ASCII tables inside code blocks

.docx generation goes through the docx skill’s script pipeline; see Word documents for its limits. If you need something you can send out as-is, ask for .pdf instead (see PDF generation).

Step 6: Accept the work

Open the file and check, in order:

Pick 5 data points at random, open the footnote URL, confirm the number is actually on that page
Confirm the contradictions section is still there and not empty
Confirm no blank cells in the matrices other than explicit “N/A” — a blank means the agent skipped it without telling you
Confirm no third-party company appears that you didn’t supply and that isn’t in the source files

Item 1 is the only check that actually validates anything. A document that reads well says nothing about whether the numbers are right.

Cost estimate

The cost shape here is worth internalizing, because it’s counterintuitive:

Step	Billing unit	Share of cost
Issuing a search	`per_call` (flat per invocation)	Small
Reading search results	`token_split` (result bodies enter context)	Large
Browser screenshot + reading it	`token_split` (image enters context)	Medium
Writing files / generating the document	`token_split` (generated text)	Medium

The dominant cost is input tokens from result bodies entering context, not how many searches you ran. So the effective lever is reducing how much body text each search brings back (narrow dimensions, restrict source types), not reducing search count. The platform truncates oversized search results, but that’s a last line of defense against context blowout, not a cost-control mechanism. See Billing formulas and Web search.

Boundaries and failure modes

Symptom	Cause	Fix
Search returns nothing	Site blocks crawling, or content is JS-rendered	Switch to the browser tool; if still unreachable, treat as publicly unavailable
Page requires login	The sandbox browser has none of your logins	Screenshot it yourself, or connect your own browser via the Chrome extension
Suspiciously round numbers in tables	The model filled a gap with a plausible value	Return to step 4, require a source per cell, change unsourced cells to N/A
Run stops midway, artifacts incomplete	Conversation budget or account balance exhausted	Written files survive; top up and resume from the next dimension
Tables drawn in ASCII	Real tables weren’t requested explicitly	Ask for native docx tables and regenerate that section
Cited URLs are dead	Source page changed or was removed	Have the agent re-verify with a fresh search and note the retrieval date

Variations

Turn it into ongoing tracking

Freeze steps 2-5 into a single prompt and run it weekly as a scheduled task to produce a “what changed this week” delta. Scheduled tasks spend credits while you’re not watching, so price a single run first — see Daily briefing.

Package it as a reusable skill

If you’ll run this repeatedly, have the agent write the flow into a skill so next time you only supply the competitor list. See Skills catalog for ownership and scope.

Publish it as a site instead

Comparison matrices read far better on the web than in Word. See Publish a site.

Web search

Search billing and truncation guards

Word documents

What docx generation can and can’t do

Browser automation

Three-layer browser architecture and login boundaries

Billing formulas

Full algorithms for all five billing units

Get Started

Core Concepts

Guides

Platform & Account

Deep Dive

End-to-end: Competitive research report

What you’ll get

Prerequisites

Steps

Step 1: Fix the framework before searching

Step 2: Search one dimension at a time and write to disk

Step 3: Handle what can’t be reached

Step 4: Cross-check and surface contradictions

Step 5: Produce the document

Step 6: Accept the work

Cost estimate

Boundaries and failure modes

Variations

Web search

Word documents

Browser automation

Billing formulas

​What you’ll get

​Prerequisites

​Steps

​Step 1: Fix the framework before searching

​Step 2: Search one dimension at a time and write to disk

​Step 3: Handle what can’t be reached

​Step 4: Cross-check and surface contradictions

​Step 5: Produce the document

​Step 6: Accept the work

​Cost estimate

​Boundaries and failure modes

​Variations

​Related pages

Web search

Word documents

Browser automation

Billing formulas

What you’ll get

Prerequisites

Steps

Step 1: Fix the framework before searching

Step 2: Search one dimension at a time and write to disk

Step 3: Handle what can’t be reached

Step 4: Cross-check and surface contradictions

Step 5: Produce the document

Step 6: Accept the work

Cost estimate

Boundaries and failure modes

Variations

Related pages