The server integrates with Authelia for OAuth-based authentication, enabling circle-based access control for HTTP clients.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@boris-mcp how does Boris handle always-on systems?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A public MCP server about Boris Churzin (essl) — what he builds, how he decides, and the ops doctrine he runs on. Point an agent at it and interrogate the judgment instead of parsing a PDF.
uvx boris-mcpOr in an MCP client config:
{
"mcpServers": {
"boris": { "command": "uvx", "args": ["boris-mcp"] }
}
}On always-on systems (design_decisions("dumb-evaluator")):
An always-on process is the one that runs when you are asleep and cannot supervise it. Every capability you give it is a capability that acts unsupervised. So the always-on half evaluates predicates and sends alerts; all judgment lives in the supervised half, which compiles rules for it.
On tracking work (doctrine("ack-is-not-answer")):
An acknowledgment is not an answer, and may be a disguised blocker. Auto-replies arrive in seconds and mean nothing happened.
That's the whole idea: ask the questions, get the reasoning. The rest is how the server serves it safely — which turns out to be the same discipline the answers are about.
Related MCP server: Graph
Nine tools are public — no auth required, callable over stdio (uvx boris-mcp) or anonymously
over HTTP:
Tool | What it gives you |
| Who, what, and the shape of the rest |
| What you can do here, and what to do next |
| Who the server thinks you are, and what that gets you |
| What's shipped since a cursor you keep — poll this at session start |
| Systems built — and what's architecturally notable about each |
| How things were actually decided, and why |
| Personal-ops rules, each with the failure it prevents |
| Languages, patterns, engineering discipline |
| How to reach him |
Beyond these, eight more tools exist behind authentication and the circles-of-trust gate: a
headhunter-tier pair (send_message, my_messages) for leaving the owner a message and
checking for a reply, and an owner-tier set (inbox, reply, grant, revoke,
access_requests, activity) for reading and answering the mailbox and managing who's let
in. See Circles, auth, and the mailbox below.
Public tools are read-only over a public corpus. The consent-carrying set above mutates
access or mailbox state — but only because the caller has already been proven to be the
owner (or, for send_message, an authenticated non-anonymous caller) by a fail-closed gate:
an unmapped or unauthenticated caller resolves to the public tier and nothing more, by
construction, not by policy. Content above the commit boundary — the private corpus — lives
off-repo on the operator's own disk and is served only through that same gate.
Access is a ladder of circles, outer to inner, each one trusted with strictly more than the last; a caller sees content gated at or below its own resolved circle and nothing above it — not even that a deeper circle exists.
flowchart LR
A["agent / caller"] -->|"stdio (uvx): offline, no auth"| P["public tier"]
A -->|"HTTP: OAuth via Authelia"| RC["resolve circle<br/>(a signed claim can only<br/>lower trust, never raise)"]
P --> G{"circle gate<br/>fail-closed"}
RC --> G
G -->|"at / below your circle"| C["public corpus in-repo<br/>+ private corpus off-repo"]
G -->|"above your circle"| D["honest denial<br/>(logged to activity)"]
C --> M["mailbox & event log<br/>pull + cursor, no push"]public is the anonymous default; everything at or above the commit boundary lives only in a
private corpus file on the operator's own disk, never in this repo. The stdio path
(uvx boris-mcp) always resolves to public. Over HTTP, a caller authenticates via OAuth
against an Authelia instance the operator runs, and the server clamps whatever circle the
token claims to what an explicit grant actually gives it — a signed claim can lower your
trust, never raise it. Forget to label a piece of content and it fails closed to owner
(the top of the ladder), hidden from everyone but the operator.
Full picture: docs/ATP.md is the acceptance-test checklist behind every locked decision (published for transparency; it reads like internal QA scaffolding, because it is), and deploy/README.md runs the HTTP + Authelia stack yourself.
The message-passing here is the reference implementation of MCPP — the Model Context
Peering Protocol (docs/MCPP.md), a formal MCP extension (SEP-style) for
agent-to-agent messaging: MCP servers peer with each other the way SMTP MTAs do, with
pull-based delivery and a trust ladder. MCPP is to MCP what SMTP is to TCP — an application
protocol over a transport that already exists. The mailbox tools
(send_message/inbox/reply/my_messages) are what's built and running today;
docs/MESSAGES.md is the implementation-level walkthrough. The spec also
defines a consent-gated ask operation — an agent drafts an answer only from what the
asker is already cleared to see, and a human discloses it — which is specified but not yet
implemented here.
There is no push, and that is deliberate. Call whats_new() at the start of a session; it
returns everything after your cursor and hands you a fresh one. There's also an
Atom feed for anything that isn't an agent.
Short version of why: MCP notifications are session-scoped and non-durable, a stdio server has no inbound network path, and the clients that matter don't implement subscriptions anyway — so push would drop any event fired while you had no session open, which is most of them. A cursor makes polling exact. The long version has the spec citations.
The reusable half lives in src/boris_mcp/_engine/ — the event log
with cursor semantics, and Atom feed generation. It knows nothing about me: a test walks its
import graph and scans its code for personal nouns, so it stays extractable
(tests/test_engine_boundary.py).
The tool surface deliberately isn't abstracted. about() / projects() /
design_decisions() is a good convention and a bad framework — a photographer wants a
portfolio, a writer wants a bibliography. Abstract the plumbing, template the surface.
Today that means: fork this, replace content.py and events.json, keep _engine/.
It'll be extracted as an installable package when someone actually wants that — see docs/GENERIC-SPLIT.md for the full split and why the repo keeps a personal name while the engine won't.
Two linter families for personal-ops text, both built and tested in
_engine/opslint/. leak is a deterministic pre-publish
check for anyone running a public server like this one — because the dangerous part of
publishing a personal MCP isn't the code, it's the day you paraphrase something you
shouldn't — and it's already wired in as scripts/leak_check.py,
run by hand before every push. hygiene flags outbound items with no follow-up date,
acknowledgments recorded as answers, statuses older than their own chase dates, and
prepared-but-unsent work; the engine and its tests exist, but it isn't exposed as a callable
MCP tool yet — that's what's coming.
This repo is a personal instance, not a framework. The instance layer (content.py,
events.json, the tool surface) is meant to be forked, not contributed to — see
CONTRIBUTING.md. Genuine bug reports against the generic engine
(_engine/) are welcome.
MIT
Who Boris is and what he builds. Start here.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden. It discloses the tier as 'public' (indicating no access restrictions) but does not explicitly state that the tool is read-only or has no side effects. For a parameterless info tool, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two short sentences) with no wasted words. It immediately conveys the core purpose and a usage hint ('Start here'), making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (no parameters, no output schema, no annotations), the description is largely complete. It explains the tool's purpose and access level. However, it could briefly mention the nature of the output (e.g., 'returns a text description of Boris and his projects') for more completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100%. The description adds no parameter meaning because none exist. Per guidelines, baseline for 0 parameters is 4, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides information about 'who Boris is and what he builds.' It includes a directive 'Start here,' distinguishing it from sibling tools like 'whoami' (likely about current user) and 'guide' (a guide). The purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies initial usage with 'Start here,' but lacks explicit guidance on when to use this tool versus alternatives like 'whoami' or 'guide.' No exclusions or context are provided, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Who has asked for access and what happened to them.
Every authenticated subject the server has never seen before gets one line here, once,
the first time it calls anything. status defaults to 'pending' — the ones still
waiting on you; pass status="" for the full history including your own grants and
revocations.
since is a cursor with the same semantics as whats_new(): pass back the cursor from
a previous call (the id of the last request in that page) and get only what arrived after
it, oldest first. Keep polling while count == limit to drain the whole backlog gap-free.
Tier: owner.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | No | ||
| status | No | pending |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses read-like behavior (listing), default status, pagination mechanics, and owner tier. Doesn't explicitly state safety (e.g., read-only), but implies it. Good detail for a list endpoint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three paragraphs, appropriately front-loaded with core purpose. Some repetition (e.g., 'the ones still waiting on you'), but overall efficient. Could be slightly more compact, but not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 params, no output schema, and no annotations, the description covers purpose, parameter behavior, pagination, and tier. Lacks explicit return value description, but for a list tool it's reasonably complete. Validates well against complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, making description essential. It explains status default and filtering, since cursor semantics (referencing whats_new), and hints at limit via 'count == limit' pagination. Adds significant value beyond bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists access requests and their status ('Who has asked for access and what happened to them'). It distinguishes from sibling tools like grant/revoke by focusing on listing rather than modifying.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides specific guidance: every new subject gets a line, status defaults to 'pending', use status='' for full history, and cursor-based pagination with since. Lacks explicit mention of when to use alternatives like grant/revoke, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The shenanigans log: every denied tool call, and every access decision you made.
This is the signal that somebody is probing the edges — a caller repeatedly asking for things above their circle shows up here as a run of denials with their subject on it. Nothing is redacted; the denial the caller received was deliberately vaguer than the line written here.
kind filters: 'denial' | 'assignment' | 'revocation'. since is a cursor (the id of the
last entry in the previous page); pass it back to get only what arrived after it, oldest
first, and keep polling while count == limit to drain the whole backlog gap-free.
Tier: owner.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | ||
| limit | No | ||
| since | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fully discloses behavior: it records denials, assignments, revocations; notes redaction difference; explains cursor-based pagination and polling mechanics. Transparent about what the tool does and its quirks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with opener, content, filter details, pagination note, and tier. Somewhat verbose but each sentence adds value. Could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description explains what entries contain (subject) and pagination behavior. Might miss full return structure but sufficient for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema coverage, description explains kind (denial/assignment/revocation) and since as a cursor. Limit is not described but has a sensible default. Overall adds significant meaning beyond raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it logs 'every denied tool call, and every access decision you made'. This is specific and distinguishes it from siblings like grant/revoke which manage access, while activity records them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explains how to use filters (kind, since) and pagination (polling while count==limit). However, lacks explicit guidance on when to use vs alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
How to reach Boris.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions 'Tier: public' which hints at access level, but does not disclose behavioral traits like side effects, idempotency, or what the tool returns. Without annotations, the description carries full burden and is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two short sentences. It could include more detail without harming conciseness, but it is efficiently written for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no parameter descriptions, so the description should explain what the tool returns (e.g., contact methods). It only states 'How to reach Boris' without specifying the output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters are defined, so baseline is 4. The description adds no param information, which is acceptable given zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'How to reach Boris' clearly communicates the tool's purpose: providing contact information for Boris. It is specific enough to distinguish it from other tools like 'about' or 'whoami'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description only states the purpose, with no context about scenarios or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
How Boris actually decided things, and why — an ADR corpus rather than a resume. Call with no topic to list them all; pass a topic key for one. Topics: dumb-evaluator, circuit-breakers-in-code, autonomy-tiers, structural-not-promised, containment-by-subtraction, state-in-files, receipt-is-not-outcome, value-not-quantity.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description fully discloses behavior: listing all records or a specific one. No mention of destructive actions, so it's appropriately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a list of topics; the first sentence is slightly figurative but still informative. Every part is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one optional parameter and no output schema, the description covers all needed information: modes of use, available topics, and the tool's nature (ADRs).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description adds complete meaning to the 'topic' parameter by listing all valid topics and explaining its use (empty for all, key for one).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's about design decisions as an ADR corpus, distinct from siblings like 'guide' or 'about'. It specifies retrieving all topics without a topic or a specific one with a key.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use: 'Call with no topic to list them all; pass a topic key for one.' While it doesn't state when not to use, the context is clear enough for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The personal-ops doctrine: rules for running your life or your agents out of files
without threads dying quietly. Each rule carries why it exists and what a linter would
check. Call with no argument for all. This is the rule set ops-lint's hygiene family
enforces against tracker files.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
| rule | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It indicates this is a retrieval tool (no side effects implied) but does not mention auth, rate limits, or response details. The phrase 'without threads dying quietly' adds some context but is not explicit about safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences plus a tier line) and front-loaded with purpose. Every sentence adds value except possibly 'Tier: public' which is redundant. No wasted text, but could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description should clarify return values. It mentions each rule has why and lint check but not structure or format. For a simple retrieval tool with one optional parameter, it is moderately complete but lacks detail on response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It states 'Call with no argument for all' for the optional rule parameter, but does not explain allowed values, format, or how specific rules are specified. The default value is hinted but semantics are minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that doctrine is a set of rules for running life or agents out of files, with each rule including rationale and lint checks. It distinguishes itself from siblings like guide and about by specifying its focus on ops-lint's hygiene rules, making the purpose specific and identifiable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage instruction ('Call with no argument for all') but does not provide when-not-to-use or compare with alternative tools. The context implies it is for retrieving doctrine rules, but lacks exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Assign a subject to a circle. Consent-carrying: calling this IS the approval.
subject is the sub claim exactly as it appears in access_requests(). The assignment
takes effect on that subject's next call and outranks whatever circle claim their token
carries — the mapping file is the operator's word, the claim is only the issuer's.
Tier: owner.
| Name | Required | Description | Default |
|---|---|---|---|
| circle | Yes | ||
| subject | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and discloses key behaviors: the call itself constitutes approval ('consent-carrying'), the assignment takes effect on the subject's next call, outranks token claims, and requires owner tier. This goes beyond basic description, though some details (e.g., error cases) are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence for the main action, followed by focused explanatory details. Every sentence adds value with no redundancy. Front-loaded with the core operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, no output schema, and no annotations, the description covers behavior, auth requirement ('Tier: owner'), and parameter semantics for subject. It lacks return value or confirmation details, but overall provides sufficient context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It explains 'subject' as the 'sub' claim from access_requests(), adding precision. However, 'circle' receives no additional meaning beyond its name. The description provides partial value but not full parameter clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Assign a subject to a circle'), specifying the verb and both resources. It distinguishes the tool from siblings like 'revoke' (opposite action) and 'access_requests' (viewing requests), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for granting circle membership, contrasting with 'revoke' for removal, but it does not explicitly state when to use or avoid this tool. No alternatives or exclusions are mentioned among the 17 sibling tools, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
What you can do here, and what to do next — the front door to self-awareness.
Derived entirely from the live tool registry (gate.TOOL_TIERS / gate.REGISTRATIONS), so it can never describe a tool the gate would refuse, or leave out one it would allow. whoami() answers "who am I"; this answers "what can I do, and what's my next step." The one caller who reaches every circle additionally gets a live operational runbook — pending access requests with copyable grant() calls, a shenanigans signal, private- corpus content health, and the publish/deploy checklist.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool is dynamically derived from the registry, cannot describe refused tools, and that special callers get additional runbook content. It does not cover auth or rate limits, but for a 0-parameter info tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative and well-structured, with the main purpose front-loaded. It includes multiple relevant details but could be slightly more concise without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the tool's return in general terms (answers 'what can I do' and 'next step', plus runbook for special callers). It is largely complete for its role as a guide, though the exact format of the response is not specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema coverage, the baseline is 4. The description adds meaning by explaining what the tool returns and its dynamic nature, going beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as a guide to what the user can do and next steps, and distinguishes it from the sibling whoami by explicitly contrasting 'what can I do' vs 'who am I'. It also positions itself as the entry point ('front door').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is the first tool to consult and differentiates from whoami, but does not explicitly state when to use it over other siblings like about or projects. The guidance is clear but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Every inbound message, oldest-first within a page. This is the owner's read of the mailbox strangers' agents write into with send_message() — cursored the same way whats_new() and access_requests() are.
since is a cursor from a previous call (the id of the last message in that page); pass it
back to see only what is new, oldest first. Keep polling while count == limit to drain
the whole backlog gap-free.
Tier: owner.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses ordering (oldest-first), pagination (cursor-based 'since' parameter), polling behavior ('keep polling while count == limit'), and access tier ('Tier: owner'). It implies a read-only operation ('owner's read'). However, it does not describe the output message structure or mention rate limits or error cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and uses three concise paragraphs. Every sentence adds value: purpose, cursor pattern, polling, and access tier. Minor redundancy (e.g., 'oldest first' mentioned twice) does not detract significantly. Could be slightly tighter but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description should cover what the agent needs to invoke and interpret results. It covers the invocation pattern well (cursor, polling) but lacks details on the message structure returned (e.g., fields, formats). This gap reduces completeness for an agent that must parse the output. However, for a simple list tool with known sibling patterns, it is partially sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It thoroughly explains the 'since' parameter as a cursor from previous calls and its usage for incremental reads. It mentions that 'limit' defaults to 50 and implies its role in pagination. A full description of 'limit's meaning could be added, but the explanation is adequate for a simple pagination pattern.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Every inbound message, oldest-first within a page', specifying the verb (list/read) and resource (inbound messages from strangers). It distinguishes from siblings like send_message (write) and my_messages (own messages) by positioning itself as the owner's read of messages sent by strangers via send_message().
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: use this to read inbound messages from strangers, and mentions cursor pattern shared with whats_new and access_requests. While it doesn't explicitly list when not to use it or provide alternatives, the sibling tool names and description give enough context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Replies addressed to you, oldest-first within a page. Poll this at the start of a session, the same way whats_new() polls the event log — if the owner answered a message you sent, it shows up here, never pushed.
since is a cursor: pass back the cursor a previous call returned (the id of the last
reply in that page) and get only what arrived after it, oldest first. Keep polling while
count == limit to drain the whole backlog gap-free. Isolation is structural, not a filter
you can turn off: this only ever returns replies whose to matches your own resolved
subject, which this server derives from your verified caller identity, never from an
argument.
Tier: headhunter.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavior: returns only replies to you, oldest-first, cursor-based pagination, structural isolation, and identity derivation. It lacks explicit mention of authentication but implies it via 'verified caller identity'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the purpose, followed by pagination details and isolation. It is slightly verbose but each sentence adds value, and the structure is logical.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with no output schema, the description covers core functionality, pagination, and isolation. It could mention return fields (e.g., reply structure), but overall it is complete enough for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds meaning: explains 'since' as a cursor from previous calls and 'limit' as page size with default 20. This compensates well for the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns replies addressed to you, oldest-first. It distinguishes from siblings like 'inbox' (all messages) and 'send_message' by focusing on replies to the user only, similar to 'whats_new' but for replies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises polling at the start of a session like 'whats_new'. It explains pagination with the 'since' cursor and how to drain the backlog. However, it does not explicitly list when not to use it or name alternative tools for other scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Systems Boris has built. Each entry says what it is and — more usefully — what is architecturally notable about it. Set include_private=False for public repos only.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
| include_private | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It mentions the parameter behavior and indicates a 'Tier: public' access level, but does not explicitly state whether the operation is read-only or if there are any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences plus a one-word line. The first sentence immediately conveys the tool's purpose, and every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with one parameter and no output schema, the description covers the essential purpose and parameter behavior. It could mention the output format briefly, but it's nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 0%, so the description compensates by explaining the practical effect of the only parameter (include_private=False for public repos). This adds clarity beyond the schema's default value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists systems Boris has built, each with architectural notes, making its purpose immediately understandable. It distinguishes itself from sibling tools like 'about' or 'whoami' by focusing on specific projects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its many siblings. It only gives a parameter hint (include_private=False for public repos), but does not explain selection criteria relative to other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Answer a message. Consent-carrying, like grant(): there is no queue or draft state — calling this IS the send, because the caller has already been proven to be the owner by the gate.
to is the from subject exactly as it appeared in inbox(); the reply lands in that
subject's my_messages() on their next poll. thread should echo the thread you are
answering so the conversation stays together; a blank thread starts a fresh one.
Tier: owner.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | ||
| body | Yes | ||
| thread | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behaviors: immediate send (no queue/draft), consent-carrying, caller must be owner, reply lands in recipient's my_messages. With no annotations, it carries the burden well, though could mention rate limits or further auth details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Efficiently uses a few sentences to convey purpose, comparison, parameter details, and tier. Front-loaded with 'Answer a message.' Could be slightly more structured, but no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity and lack of output schema, it explains the interaction with inbox/my_messages and the immediate nature. Missing error conditions, but overall sufficient for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning to 'to' and 'thread' (explaining source and threading). However, 'body' receives no additional description beyond the schema name, and schema coverage is 0%, so description only partially compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Answer a message' as the verb and resource, distinguishing it from sending new messages (sibling send_message) by emphasizing it as a reply. However, it does not explicitly differentiate from send_message, so it's not a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides some guidelines: 'to' must be from inbox, 'thread' should echo the conversation. But lacks explicit when-to-use vs alternatives like send_message, and no when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Remove a subject's circle assignment. Consent-carrying: calling this IS the approval.
The subject does not become unknown again — their request line stays in the log, and they fall back to whatever an unmapped authenticated caller gets. Revoking somebody who was never assigned is a no-op that still records the intent.
Tier: owner.
| Name | Required | Description | Default |
|---|---|---|---|
| subject | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the burden. It discloses that the call is consent-carrying, explains the subject's fallback state, and clarifies that revoking a never-assigned subject is a no-op. This provides useful behavioral context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences plus a tier label, with the main action front-loaded. Almost no wasted words, though a more structured format with an explicit parameter definition would be ideal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers key behavioral aspects (consent, no-op, tier), but lacks details on return values, error conditions, or preconditions (e.g., must be an existing user). With no output schema or annotations, these gaps reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage, the description must define the parameter. It introduces 'subject' but does not explicitly describe what it represents (e.g., a user ID or identifier). The context implies it's the entity to revoke, but the definition is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Remove a subject's circle assignment.' It uses a specific verb and resource, and effectively distinguishes from sibling tools like 'grant' (add assignment) and 'access_requests' (list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context about consent (calling this IS the approval) and behavior for non-assigned subjects (no-op that records intent). It also specifies 'Tier: owner' indicating who should use it. However, it does not explicitly mention alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Leave a message for the owner. Pull-based, like whats_new(): there is no push, the owner reads this via inbox() on their own schedule, and any reply shows up in my_messages() the next time you poll it.
body is stored and returned as opaque text — write whatever you want a human to read.
It is capped at 4000 characters and is never interpreted, templated, or executed by this
server or by anything that displays it.
thread is a conversation key you choose; leave it blank to start a new one and reuse
the value you get back to keep a conversation together. Sending is rate-limited per
caller so one subject cannot bury the owner's inbox before they have looked at it once.
Tier: headhunter.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | ||
| thread | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It details that body is opaque text, capped at 4000 chars, never interpreted; thread is a user-chosen conversation key; rate limiting per caller; and that this is pull-based with no push.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is slightly lengthy but well-structured with front-loaded purpose and subsequent behavioral details. Each sentence adds value, though some redundancy could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only two parameters and no output schema, the description covers all necessary aspects: purpose, parameter behavior, rate limits, and interaction model. No information gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description fully explains both parameters: body is opaque text with a 4000-character cap, thread is a conversation key with instructions to leave blank for new or reuse for continuity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Leave a message for the owner' and distinguishes this pull-based tool from siblings like inbox() and my_messages(). It explains the communication pattern without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for usage (sending a message) and explains the pull-based nature with references to inbox() and my_messages(). Does not explicitly state when not to use, but the purpose is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Languages, architectural patterns, and engineering discipline — the checkable kind.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only mentions 'Tier: public' which hints at access, but does not disclose whether the tool reads data, checks code, or produces output. No side effects or behaviors are described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences) and front-loaded, but it sacrifices clarity for brevity. The information is minimal and could be more informative without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and multiple siblings, the description should clarify what this tool uniquely offers. It fails to differentiate from 'guide', 'doctrine', or 'projects', making it incomplete for an agent to decide which tool to invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so there is nothing to add beyond the schema. The description provides some context about the tool's content (languages, patterns, discipline), which is acceptable for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Languages, architectural patterns, and engineering discipline — the checkable kind' is abstract and does not clearly state what action the tool performs or what resource it provides. It could be documentation, a linter, or a reference, but the purpose is vague, especially when compared to siblings like 'guide' or 'doctrine'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus its siblings. Among tools like 'guide', 'doctrine', and 'design_decisions', there is potential overlap, but no explicit when/when-not or alternative mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
What Boris has shipped or published, oldest-first within a page. THIS IS THE SUBSCRIBE-EQUIVALENT: call it once when a session starts, and again whenever you want to catch up. It is a forward log, not a "most recent N" snapshot.
since is a cursor — pass either an event id or an ISO-8601 timestamp from a previous
call, and you get only what came after it, OLDEST first. Every response includes a cursor
field (the id of the last event in THIS page); keep it and pass it back next time. To drain
a backlog, keep polling with the returned cursor while count == limit — a full page means
more unseen events remain behind it. Passing nothing returns the OLDEST limit events,
then poll forward to reach the present.
kind optionally filters: 'release' | 'project' | 'writing' | 'note'.
There is deliberately no push/subscribe mechanism — see the delivery field in the
response, and docs/EVENTS.md. Poll this on session start; that is the intended use.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | ||
| limit | No | ||
| since | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses behavior: oldest-first ordering, cursor-based pagination, effect of passing nothing, and the need to poll for backlog. It also notes the absence of a push mechanism, making the tool's read-only nature clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a summary sentence, followed by detailed but compact explanations for each aspect. Every sentence adds value, and the tier indicator is a useful extra touch. It is as concise as possible given the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description mentions key response fields (cursor, delivery) and references external documentation. It covers the core mechanics, but could provide a bit more structure for the response format. Still, it is largely complete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description explains all three parameters: `since` as cursor (id or timestamp), `kind` with enumerated filter values, and `limit` with default 20. It also explains the interaction between cursor and limit for pagination.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly defines the tool as a forward log of shipped/published items, oldest-first, with a subscribe-equivalent usage. It distinguishes from typical 'most recent N' snapshots and sibling tools like guide, contact, or projects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to call it: on session start and to catch up. Provides detailed polling instructions with cursor, including how to drain backlog. Mentions no push/subscribe mechanism and references additional documentation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Who this server thinks you are, and what that gets you.
Returns the subject your token carries — or "anonymous", which covers both a local
stdio session and an authenticated HTTP call whose token simply carries no subject
claim — the circle you resolved to, and whether an access request is on file for you.
circles lists the ones your own circle reaches — there may be others, and if there
are, the response says so without naming them.
Tier: public.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the tool's behavior well: it returns the subject, circle, and access request flag, and clarifies the 'anonymous' case. It also mentions that additional circles exist but are not named, showing transparency about response limitations. With no annotations, the description carries the full burden and largely meets it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise, with the main purpose front-loaded in the first sentence. It provides necessary details without excessive verbosity. Minor improvements could tighten phrasing, but it is effective and not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description fully explains the tool's output components (subject, circle, access request) and addresses edge cases (anonymous, unlisted circles). With no output schema, the description must cover the return value semantics, and it does so comprehensively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is trivially 100%. The description adds value by explaining what is returned, which is relevant context despite no parameter documentation being needed. The baseline for 0 parameters is 4, and the description meets that expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: returning who the server thinks you are and what capabilities that grants. It explicitly lists the return values (subject, circle, access request status) and explains edge cases like 'anonymous'. This distinguishes it from sibling tools like 'about' or 'guide', which serve different informational purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for identity and authorization checks, but it does not explicitly state when to use this tool versus alternatives. No guidance on when not to use it or prerequisites is provided, which is acceptable given its simplicity. However, explicit usage context would improve the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0aboutaccess_requestsactivitycontactdesign_decisionsdoctrinegrantguideinboxmy_messagesprojectsreplyrevokesend_messagestackwhats_newwhoamiEach tool targets a distinct resource or action: informational (guide, about, whoami), knowledge (projects, design_decisions, doctrine), messaging (send_message, my_messages, inbox, reply), and administration (access_requests, grant, revoke, activity). No two tools have overlapping purposes.
All tool names follow a consistent pattern of lowercase snake_case, with single words or underscore concatenations (e.g., design_decisions, send_message, access_requests). No mixing of conventions like camelCase or PascalCase.
17 tools is slightly above the typical well-scoped range (3-15), but each tool covers a necessary function for the server's stated purpose (personal knowledge, updates, messaging, access control). The count feels justified given the comprehensive scope.
The tool set covers all apparent use cases: getting to know Boris (guide, about, projects, design_decisions, doctrine, stack), staying updated (whats_new), communicating (send_message, my_messages, inbox, reply), and managing access (access_requests, activity, grant, revoke). No critical gaps are present.
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An MCP server for deep research or task groups
MCP server for agentverse documentation, generated by doc2mcp.
MCP server for building and testing AI agents with multi-model experimentation and insights.
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