Skip to main content
Glama

cos_trajectory_snapshot

Persist a project trajectory snapshot with phase, focus, architectural decisions, anti-patterns, and open questions to give future sessions context beyond task history.

Instructions

Persist a project trajectory snapshot for the current session.

Records WHERE the project is heading (phase, focus, architectural decisions, anti-patterns discovered, open questions) so future sessions have strategic context beyond task history. Each call creates a new row linked to the previous snapshot via supersedes_id.

Args: session_id: Current session identifier. phase: Current development phase (e.g. "v2 hardening"). current_focus: What the team is focused on right now. architectural_decisions: JSON array of {decision, rationale} objects. anti_patterns_discovered: JSON array of {pattern, context} objects. open_questions: JSON array of {question, priority} objects or plain strings. next_logical_step: Single-sentence description of what comes next. confidence: Confidence in this trajectory assessment (0.0-1.0).

Returns: JSON with {status, id, supersedes_id}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
phaseNo
confidenceNo
session_idYes
current_focusNo
open_questionsNo[]
next_logical_stepNo
architectural_decisionsNo[]
anti_patterns_discoveredNo[]

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

While annotations already indicate a write operation (readOnlyHint=false), the description adds valuable behavioral context: each call creates a new row linked to the previous via supersedes_id, implying an append-only chained structure. It also discloses the return payload (status, id, supersedes_id).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with an intro, Args block, and Returns block. It is reasonably sized for 8 parameters and provides essential detail without fluff. Slightly verbose but acceptable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 params, output schema exists), the description is thorough: it explains each parameter, the linking behavior, and the return format. It is complete enough for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden. It provides meaningful interpretations for each parameter, e.g., 'architectural_decisions: JSON array of {decision, rationale} objects' and 'confidence: Confidence in this trajectory assessment (0.0-1.0)'. This goes well beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action ('Persist') on a specific resource ('project trajectory snapshot') for the current session. It also distinguishes itself from the sibling tool 'cos_trajectory_read' by focusing on writing/persisting rather than reading.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains the purpose ('so future sessions have strategic context') and implicitly positions itself as the write counterpart to cos_trajectory_read. However, it does not explicitly state when not to use it or mention alternatives beyond the implied read tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kouroshez/coding-os'

If you have feedback or need assistance with the MCP directory API, please join our Discord server