ShotPulled

Update a shot

update_shot

Idempotent

Correct fields on an already-logged shot in place — no need to delete and re-log. Use for fixing a wrong dose/yield/time or grind label, re-filing a shot onto the right bean (bean_id), backfilling rating/tasting notes, or fixing the timestamp (pulled_at). Changing grind_label re-derives the numeric grind position from the shot's grinder; changing yield/time/dose/tds keeps flow rate and extraction yield consistent automatically.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`fields`	Yes	Only the fields to change
`shot_id`	Yes	ID of the shot to correct

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`message`	Yes
`shot_id`	Yes
`updated_fields`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedAug 17, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "message": {
+      "type": "string"
+    },
+    "shot_id": {
+      "type": "integer"
+    },
+    "status": {
+      "type": "string"
+    },
+    "updated_fields": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "status",
+    "shot_id",
+    "updated_fields",
+    "message"
+  ],
+  "type": "object"
+}

Changed9 schema fields changedJul 19, 2026

addedInput schema / properties / fields / properties / data_confidence / description

Added value: +"estimated marks the metrics as a best guess instead of burying the caveat in notes"

changedInput schema / properties / fields / properties / data_confidence / enum

Previous value: -[
-  "measured",
-  "recalled"
-]New value: +[
+  "measured",
+  "recalled",
+  "estimated"
+]

addedInput schema / properties / fields / properties / flavor_notes / description
```
Added value: +"null clears the notes"
```
changedInput schema / properties / fields / properties / flavor_notes / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
addedInput schema / properties / fields / properties / rating / description
```
Added value: +"1-5; null clears the rating"
```

changedInput schema / properties / fields / properties / rating / type

Previous value: -"integer"New value: +[
+  "integer",
+  "null"
+]

addedInput schema / properties / fields / properties / tasted

Added value: +{
+  "description": "Backfill 1 to mark a pending shot as tasted-clean (tasted, no defect tags) so it leaves the taste-pending queue without inventing a tag or rating",
+  "enum": [
+    0,
+    1
+  ],
+  "type": "integer"
+}

addedInput schema / properties / fields / properties / verdict / description
```
Added value: +"null clears the verdict"
```
changedInput schema / properties / fields / properties / verdict / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```

AddedJul 14, 2026

TDQS

A4.9/5.0

Behavior5/5

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

The description discloses meaningful behavioral side effects beyond the annotations: changing grind_label re-derives the numeric grind position from the shot's grinder, and changing yield/time/dose/tds automatically keeps flow rate and extraction yield consistent. It also makes clear this is an in-place mutation ('correct fields... in place'), which complements the idempotentHint and destructiveHint annotations. No contradiction with annotations exists.

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

Conciseness5/5

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

The description is compact and front-loaded: it states the core purpose in the first clause, then gives concrete usage examples, and finishes with the most important behavioral caveats. Every sentence earns its place, and nothing is redundant with the schema or annotations.

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?

The description is complete for a two-parameter tool with a nested fields object. It explains the correction workflow, highlights which field changes trigger automatic recalculation, and gives enough use-case context for an agent to decide when to call it. Since an output schema exists and all parameters are documented in the input schema, the description does not need to restate return values or field types.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds important cross-field semantics: grind_label re-derives the grind position and yield/time/dose/tds changes trigger automatic consistency adjustments. These meanings are not visible from individual schema property descriptions. The description also frames fields like bean_id, pulled_at, and grind_label with purposeful examples rather than just type definitions.

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 states a specific verb and resource: 'Correct fields on an already-logged shot in place.' It clearly distinguishes the tool's purpose from delete_shot and log_shot by explicitly saying 'no need to delete and re-log.' Concrete use cases ('fixing a wrong dose/yield/time or grind label, re-filing a shot onto the right bean') make the purpose unmistakable.

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

Usage Guidelines5/5

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

The description gives explicit usage guidance: use this when correcting an existing shot instead of deleting and re-logging. It enumerates common scenarios like fixing dose/yield/time, re-filing onto a different bean, backfilling rating/tasting notes, and fixing timestamps. This tells the agent both when to reach for this tool and why alternatives like delete_shot + log_shot are not needed.

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

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TDQS

B3.4/5.0

Disambiguation4/5

Most tools target a clearly distinct resource and action, and the list/register/update/set tool families are easy to tell apart. The closest pair is diagnose_preview and diagnose_shot, which are well-described but similar enough in name that an agent could select the wrong one.

Naming Consistency4/5

The overwhelming majority of tools follow a consistent verb_noun pattern (list_beans, register_grinder, update_shot, set_active). Minor exceptions like grinder_math and kb_changelog lack the imperative verb prefix, but they are readable and do not create real confusion.

Tool Count2/5

34 tools is above the 25+ threshold and feels heavy even though the domain is fairly rich. The many parallel list_* and register_* tools for beans, grinders, machines, scales, waters, programs, and recipes could plausibly be consolidated or trimmed without losing core capability.

Completeness3/5

The core shot lifecycle is well covered: log, update, delete, diagnose, and list shots, plus bean registration and maintenance tracking. However, most registered entities lack update/delete tools, and get_rule has no corresponding list_rules tool, leaving some obvious workflow gaps that agents must work around.

Resources

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