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salesforce_learn_context

Capture and store user context, business processes, and Salesforce data model insights to provide personalized, context-aware assistance across sessions.

Instructions

Learn and store personal/business context about the user and their Salesforce data model relationships. This helps provide better context-aware assistance across sessions. PROACTIVELY CAPTURE AHA MOMENTS: Whenever you discover something important about the user's workflow, business processes, preferences, challenges, or breakthrough insights during conversations, automatically use store_learning to preserve this knowledge. Look for moments when the user reveals key information, expresses frustration, shares successful strategies, or has realizations - these are valuable learnings that should be stored immediately.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform: start_interview (begin learning), answer_question (provide answers), show_context (display stored context), reset_context (clear all), suggest_questions (get intelligent questions based on data model), quick_setup (explain everything in one go), store_learning (AUTOMATICALLY capture breakthrough insights, aha moments, user preferences, workflow patterns, pain points, or any valuable context discovered during conversation)
question_idNoID of the question being answered (when action is 'answer_question')
answerNoAnswer to the question (when action is 'answer_question')
context_typeNoType of context to focus on (for show_context and suggest_questions). Can be any section name like 'personal', 'business', 'data_model', 'technical_preferences', etc., or 'all' for everythingall
full_nameNoYour full name (for quick_setup)
emailNoYour email address (for quick_setup)
roleNoYour professional role/position (for quick_setup)
company_nameNoYour company name (for quick_setup)
industryNoYour company's industry (for quick_setup)
business_process_descriptionNoComplete description of your business processes, how you use Salesforce, what you do, etc. (for quick_setup)
sectionNoContext section to store the learning in (for store_learning). Use descriptive names that capture the nature of the insight: 'aha_moments' for breakthrough realizations, 'pain_points' for challenges discovered, 'workflow_insights' for process discoveries, 'preferences' for user likes/dislikes, 'success_patterns' for what works well, 'technical_discoveries' for system insights, etc. Will be created dynamically if it doesn't exist.
keyNoKey name for the learning (for store_learning). Use specific, descriptive names that capture the insight: 'critical_realization_about_X', 'main_frustration_with_Y', 'breakthrough_solution_for_Z', 'preferred_approach_to_A', 'discovered_workflow_pattern_B', etc. Be specific about what was learned.
valueNoValue/content of the learning (for store_learning)
overwriteNoWhether to overwrite existing values for the same key (for store_learning). Default: false
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool stores context across sessions for better assistance, proactively captures insights during conversations, and automatically triggers 'store_learning' for valuable moments. However, it doesn't cover potential limitations like storage capacity, session persistence details, or error handling.

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

Conciseness3/5

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

The description is moderately concise but could be more front-loaded. The first sentence states the core purpose clearly, but the second sentence is lengthy and repetitive, detailing proactive capture scenarios that are somewhat redundant with the schema's 'store_learning' description. Some trimming could improve efficiency without losing key guidance.

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

Completeness4/5

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

Given the tool's complexity (14 parameters, no output schema, no annotations), the description does a good job covering purpose and proactive usage. It explains the tool's role in context-aware assistance and when to invoke it, but lacks details on output format, error cases, or how stored context integrates with other tools. The schema compensates well for parameter documentation.

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

Parameters3/5

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

The schema description coverage is 100%, so the schema already documents all 14 parameters thoroughly. The description adds minimal parameter-specific semantics beyond the schema, mainly emphasizing the 'store_learning' action for proactive capture. It doesn't provide additional meaning for parameters like 'section' or 'key' beyond what's in their schema descriptions.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Learn and store personal/business context about the user and their Salesforce data model relationships' and 'helps provide better context-aware assistance across sessions.' It specifies the verb ('learn and store') and resource ('context'), but doesn't explicitly differentiate from sibling tools like 'salesforce_learn' or 'salesforce_setup' beyond the context focus.

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 provides explicit guidance on when to use the tool: 'PROACTIVELY CAPTURE AHA MOMENTS: Whenever you discover something important... automatically use store_learning to preserve this knowledge.' It lists specific scenarios (user reveals key information, expresses frustration, shares successful strategies, or has realizations) and names the specific action ('store_learning'), offering clear alternatives for other actions via the input schema.

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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