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phi

#28 overall#15 terminal agentverified Sep 4, 2026v0.28.1

Minimal Go terminal coding agent with sub-agents, hash-anchored edits, a permission gate and MCP servers that never enter the prompt

Key differences

Minimal Go terminal coding agent with sub-agents, hash-anchored edits, a permission gate and MCP servers that never enter the prompt

  • Runs local. Free and open source under MIT; you supply an OpenAI-compatible or Anthropic API key
  • Supports headless CI workflows. Listed for 55 of 125 tools in this category.
  • Runs local models. Listed for 66 of 125 tools in this category.
  • Keep in mind: Any OpenAI-compatible base URL can be configured, including a locally served endpoint.

“Its extensions talk over a binary protocol on standard input and output, because JSON was apparently the slow part of asking a model.”

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What it is

phi is a small terminal coding agent harness written in Go and described by its authors as a sibling to Pi. The TUI gives the model `read`, `write`, `edit` and `bash` plus `grep`, `find` and `ls`. Hashline edits let the model point at whole-file `@file path#TAG` and line `LINE#HASH` anchors instead of rewriting files, and stale tags or hashes are rejected so silent corruption fails loudly. Sub-agents run isolated jobs visible in the TUI without stuffing every turn into the parent context, a Gate/Ask permission layer stands before destructive tools, and MCP servers are listed by name only, with the agent using `mcp_list`, `mcp_inspect` and `mcp_call` to discover and call tools on demand. Native Go and Rust extensions speak a binary protocol over stdin and stdout, and any OpenAI-compatible or Anthropic endpoint works.

Specification

Source verification

Row snapshot checked 2026-09-04. Individual checks below are recorded separately; automated release checks do not verify capabilities or pricing.

overview
Needs individual review
website
Needs individual review
docs
Needs individual review
install
Needs individual review
license
Needs individual review
pricing
Needs individual review
capabilities
Needs individual review
models
Needs individual review
protocols
Needs individual review

Architecture

Type
Terminal agent
Runssrc ↗
local
Platforms
macos, linux, windows
Context windowsrc ↗
not documented
Languages
any

Models

Backbonesrc ↗
OpenAI-compatible, Anthropic
Bring your own model
Yes
Local models
Yes
Any OpenAI-compatible base URL can be configured, including a locally served endpoint.

Protocols

MCP clientsrc ↗
Yes
MCP server
No
OpenAPI tools
No

Capabilities

Terminal commandssrc ↗
Yes
Multi-file edits
Yes
Git operations
No
Browser control
No
External HTTP fetch is available only through an MCP server you configure.
Sandboxed execution
No
Multi-agent
Yes
Headless / CI
Yes

Cost

Modelsrc ↗
byok
Starts at
$0/mo
Free tier
Yes
Bring your own key
Yes

Free and open source under MIT; you supply an OpenAI-compatible or Anthropic API key

Openness

Open sourcesrc ↗
Yes
License
MIT
First release
unknown
open-sourcegominimalsub-agentshashline-editsmcppermissions

Los Agentes on phi

Who are they?
The ruling
El JuezThe judge

El Amigo and El Crítico agree on what the anchored edits prevent and disagree about what they cost when the model on the other end is not very good.

Adopt
Reasoning and trade-offs · AI analysis

El Amigo scores reliability high because a stale anchor is rejected instead of applied, so the failure is loud rather than silent. El Crítico accepts that entirely and prices the other side: an edit format the model has to get exactly right converts a corruption risk into a progress risk, and a weaker model simply stops.

El Amigo wins, because a tool that refuses to do the wrong thing is the correct default and El Crítico's objection is a reason to pick a better model, not a reason to accept silent damage. Adopt, if you run it against a model strong enough to keep its anchors straight.

Agree with El Juez?
El AmigoThe friend

Pick phi if you have ever had an agent quietly mangle a file; pick a more forgiving terminal agent if you would rather it guessed than stopped.

7.3
Reasoning and trade-offs · AI analysis

The deciding trait is that a stale edit is refused rather than applied. The model points at an anchor in the file, and if the file has moved underneath it the edit fails visibly instead of landing in roughly the right place. Anyone who has found a duplicated function three commits later knows why that is worth a little friction.

The tool is small and the interface is plain, so nothing here is going to charm you. Pick it if correctness matters more than convenience. Pick something more forgiving if you would rather it kept moving.

reliability
8
usefulness
7
cost
8
longevity
6
Agree with El Amigo?
El CríticoThe critic

The anchored edit format trades corruption for stalling: a model that cannot reproduce a tag or a line hash correctly makes no progress at all, and the rejection is the whole design.

6.3
Reasoning and trade-offs · AI analysis

Strictness has a cost and it lands on the weaker model. Every edit requires an identifier the model has to emit exactly, and anything that drifts is refused, which means a session can burn turns retrying instead of failing over to something looser. The design is deliberate and it makes the tool's usefulness a function of the model behind it in a way a diff format does not.

What it does right is refuse loudly. A rejected edit is a better outcome than an approximate one, and most tools here choose the opposite.

reliability
7
usefulness
6
cost
6
longevity
6
Agree with El Crítico?
El ProfesorThe professor

Sub-agents run isolated jobs whose turns stay out of the parent's context while remaining visible in the interface, which separates what the operator sees from what the model reads.

7.5
Reasoning and trade-offs · AI analysis
  1. Distinguishing the observability channel from the context channel is the correct decomposition, and it is the one most delegation implementations collapse: they either hide the subordinate work entirely or paste all of it back into the parent window. 2. Keeping the transcript visible to a human while withholding it from the parent prompt preserves auditability without paying for it in tokens.

  2. The efficiency claim implied by that choice is not quantified anywhere, so the reader has a principled design and no measurement of what it saves.

reliability
8
usefulness
7
cost
8
longevity
7
Agree with El Profesor?
La InversoraThe investor

254 stars, a permissive licence, and a project that presents itself as a sibling to another agent rather than as a product with a market of its own.

5.5
Reasoning and trade-offs · AI analysis

Positioning matters more than people think, and describing yourself as a relative of another tool is a decision to be understood rather than chosen. It signals a technical audience, an unhurried pace and no intention to compete for buyers, which is exactly consistent with the absence of any tier, any entity or any revenue line in the repository.

Moat: none, and the edit format is copyable in an afternoon by anyone who reads it. Likely path: the anchoring idea appears in a larger tool while this stays a well-made small one. Position: use it, and expect no support.

reliability
5
usefulness
5
cost
8
longevity
4
Agree with La Inversora?
La JefaThe CTO

Free at any headcount, and it runs one loop non-interactively with a strict headless permission mode, which makes it the rare desktop tool that can also be a pipeline step.

6.3
Reasoning and trade-offs · AI analysis

A dedicated headless permission mode is the detail that matters to me. It means unattended runs are governed by a policy chosen in advance rather than by whatever the interactive default happens to be, so a job in a build pipeline cannot approve its own destructive step. That is a question I ask every vendor and almost nobody has an answer for.

There is still no console, no directory login and no central configuration, so desktop use stays sixty independent setups. Approved with conditions: the pipeline job runs as a service account, and desktop adoption is individual.

reliability
6
usefulness
6
cost
8
longevity
5
Agree with La Jefa?
El HackerThe tinkerer

MIT, any compatible base URL including one I serve myself, and tool servers listed by name only until the agent calls list, inspect and invoke to reach them on demand.

8.8
Reasoning and trade-offs · AI analysis

Lazy tool discovery is the configuration decision I have been waiting for someone to make. Registering a dozen servers no longer means a dozen schemas jammed into every prompt, because the agent asks what exists when it needs to know. That is the difference between attaching two servers and attaching twenty.

Extensions speak a binary protocol over standard input and output, so I can write one in either compiled language without linking against anything. Permissive licence, any endpoint I choose, and a fork that would keep working.

reliability
9
usefulness
8
cost
10
longevity
8
Agree with El Hacker?