Do coding agents recommend Perigon?
Perigon was chosen in 2% of 499 judged AI search sessions, ranking number 12. Measured with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code.
Perigon was chosen in 2% of 499 judged AI search sessions, ranking number 12. It was also raised as a candidate in 17 further sessions without being chosen.
This page reports what happened when Claude Code, Codex, Cursor, Grok Build CLI and Muse Code had to solve a problem in AI search inside a realistic codebase. Not what a chat assistant says about Perigon. What an agent actually installed.
The numbers
| Category | AI search |
| Sessions in the category | 499 |
| Sessions where Perigon was chosen | 8 |
| Install share | 2% |
| Rank in category | 12 of 41 |
| Codebases it won in | 2 |
| Raised as a candidate, not chosen | 17 |
| Chosen when considered | 32% |
| Site | perigon.io |
By agent
With 8 wins spread across 5 agents, the rates below are small numbers and a difference between them is not yet a finding. They are here because the direction is worth knowing, not because the gap is established.
| Agent | Sessions | Chose Perigon | Share |
|---|---|---|---|
| Claude Code | 140 | 4 | 3% |
| Codex | 144 | 0 | 0% |
| Cursor | 136 | 2 | 1% |
| Grok Build CLI | 35 | 2 | 6% |
| Muse Code | 44 | 0 | 0% |
By who was asking
Perigon performs similarly across the four kinds of buyer, from 0% to 6%. That is unusual: the category leader changed with the persona in 23 of the 29 categories we measured.
| Who is asking | Sessions | Chose Perigon | Share |
|---|---|---|---|
| Vibe coder | 82 | 0 | 0% |
| Junior developer | 173 | 0 | 0% |
| Senior engineer | 124 | 1 | 1% |
| Enterprise team | 120 | 7 | 6% |
What Perigon was up against
The full ranking in AI search, from the same sessions:
| # | Product | Runs won | Share |
|---|---|---|---|
| 1 | Anthropic web search | 84 | 17% |
| 2 | Brave Search API | 69 | 14% |
| 3 | Exa | 67 | 13% |
| 4 | Tavily | 42 | 8% |
| 5 | OpenAI web search | 27 | 5% |
| 6 | Built in-house (no product adopted) | 24 | 5% |
| 7 | Firecrawl | 23 | 5% |
| 8 | NewsAPI.ai | 23 | 5% |
What this means
Perigon was raised in 17 sessions and chosen in 8. That ratio is balanced enough that the ceiling is presence rather than integration: the product converts reasonably when it is on the table, and it is not on the table often enough.
Where these numbers come from
The 499 sessions in AI search are part of a published set of 11,878, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.
Every AI search run can be replayed on the board.
If you work on Perigon: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.
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Common questions
Do coding agents recommend Perigon?
Yes. Perigon was chosen in 8 of the 499 judged sessions in AI search, a 2% install share, ranking number 12 in its category.
Does Claude Code recommend Perigon?
In 4 of the 140 sessions in AI search run with Claude Code, which is 3%.
Do different coding agents treat Perigon differently?
Not much. Claude Code, Codex, Cursor, Grok Build CLI and Muse Code chose it at similar rates, between 0% and 6% of their runs.
How was this measured?
Real coding agents at pinned versions were run in sandboxes inside 91 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.
How often is Perigon considered but not chosen?
It was raised as a candidate in 17 sessions without being chosen, and chosen in 8. That is a 32% conversion from considered to chosen.
Where this comes from
Armature ran 11,878 judged sessions with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code inside 91 realistic codebases, and published every run. The numbers on this page come from that work.