Update ingredients on hand
update_ingredientsAdd/refresh items (upsert by name), remove items, or replace the whole inventory.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| add | No | ||
| remove | No | Names to remove (used up) | |
| replace_all | No |
update_ingredientsAdd/refresh items (upsert by name), remove items, or replace the whole inventory.
| Name | Required | Description | Default |
|---|---|---|---|
| add | No | ||
| remove | No | Names to remove (used up) | |
| replace_all | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It explicitly discloses that the tool mutates inventory, upserts by name, removes items, and can replace the entire inventory, which signals destructive potential. It does not mention return values or whether replace_all supersedes add/remove, but the core side effects are 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 a single concise sentence with three clear clauses, no filler, and the core behavior front-loaded. Every word contributes to understanding the tool's purpose.
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 the primary use cases well, but with no annotations and no output schema it leaves some operation details unspecified, such as whether replace_all requires or combines with the add array, and what happens if multiple modes are supplied together. These are meaningful gaps for a destructive mutation tool.
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 description coverage is only 33%, so the description must compensate. It does by explaining the meaning of the three operations: add/refresh upsert by name, remove items, and replace the whole inventory. This gives semantic value to replace_all, which otherwise lacks a schema description.
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 states specific verbs and resources: add/refresh items, remove items, or replace the whole inventory. This clearly identifies the tool as a mutation of the ingredient inventory and distinguishes it from read-only siblings like get_ingredients.
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 clear context for when to use the tool: maintaining the current on-hand ingredient inventory via upsert, removal, or full replacement. It does not explicitly name alternatives like get_ingredients for reading or update_recipe for recipe ingredient edits, but the usage context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target a distinct resource and action, with detailed descriptions that clarify boundaries. The main confusable pair is run_agent_chef vs next_actions, which both return the due-action checklist and operating instructions, differing only by trigger context. propose_recipes vs add_candidates are also related but clearly separated by phase (initiating a cycle vs appending during feedback).
The overwhelming majority follow a verb_noun snake_case pattern (get_, update_, set_, add_, record_, remove_), which is highly predictable. Minor deviations include next_actions being a bare noun phrase rather than get_next_actions, and favorite_recipe using 'favorite' as a verb instead of something like toggle_favorite.
At 34 tools, the surface is heavy for an agent to select from, exceeding the 25+ threshold for 'too many'. The domain is genuinely broad, but several utility and meta tools (dismiss_setup_checklist, record_schedule, get_connected_agents, get_instructions) and overlapping entry points (run_agent_chef, next_actions) inflate the count and could be consolidated without losing capability.
The full weekly lifecycle is covered end-to-end: propose, vote, feedback, add candidates, lock in, shop, order, cook, rate, and mark done. Recipe, member, ingredient, and preference management all have solid get/update/create coverage. Minor gaps include no way to delete a recipe, remove a candidate from an active ballot, or cancel a week beyond reopen_voting, but these are work-aroundable and don't create dead ends.