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managed-memory

Give an agent durable, cross-session long-term memory using Databricks MANAGED memory (the Unity Catalog memory-store REST APIs) as tools — governed by UC with no infra the customer needs to run. This works for either OpenAI Agents SDK or LangGraph templates. Use when: the agent should remember a user's (or a team/org's shared) preferences/facts/decisions across conversations; keywords 'long-term memory', 'managed memory', 'memory store', 'agentic memory'. This is separate from the self-hosted Lakebase memory solution with skills in (agent-openai-memory / agent-langgraph-memory).

Quality

85%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is managed-memory in databricks/app-templates

SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Highly actionable with a well-validated workflow, but the body is verbose (notably triplicated search-query guidance) and monolithic with no progressive file splitting. Pulling the reference material into separate files and de-duplicating the search guidance would most improve it.

Suggestions

De-duplicate the self-contained search-query guidance: keep the canonical version in the search_memory docstring and have the Step 3 blockquote and Limits section reference it instead of restating it.

Move the Limits & errors reference and the Troubleshooting table into a one-level-deep reference file (e.g. references/limits.md) linked from a short inline summary, to apply progressive disclosure and shrink the SKILL.md overview.

Consider extracting the full shared-core tool implementations into references/utils_memory.py with a concise inline excerpt, so the overview stays scannable while preserving copy-paste-ready code.

DimensionReasoningScore

Conciseness

Mostly efficient and domain-specific, but the self-contained search-query guidance is repeated nearly verbatim three times (search_memory docstring, the blockquote after Step 3, and the Limits section), and the tool docstrings are long; tightening the duplication would raise this.

3 / 5

Actionability

Provides complete, copy-paste-ready OpenAI tool implementations, curl grant calls, yaml env wiring, and resolve_scope variants; the LangGraph sketch is explicitly and reasonably justified as a translation rather than standalone code.

5 / 5

Workflow Clarity

Steps 1–5 are clearly sequenced with explicit validation checkpoints (confirm-existing-store GET, grant verification, fail-closed scope guard, test curls) and error-recovery feedback loops in _search plus a troubleshooting table.

5 / 5

Progressive Disclosure

No bundle files exist and the ~620-line skill is monolithic; the full tool implementations, Limits & errors reference, and troubleshooting table are inlined content that could be split into one-level-deep reference files, though section headers provide reasonable navigation.

3 / 5

Total

16

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states capability, trigger conditions, and distinctions from sibling skills. It is slightly long and could trim some explanatory clauses, but it satisfies what/when/distinctiveness well.

DimensionReasoningScore

Specificity

Names the domain and several concrete capabilities ('durable, cross-session long-term memory', 'Unity Catalog memory-store REST APIs as tools', 'governed by UC with no infra'), with only minor coverage gaps; not quite the comprehensive multi-action list of a 5.

4 / 5

Completeness

Explicitly answers both what (give an agent durable cross-session memory via managed memory REST APIs) and when (a concrete 'Use when:' clause with trigger conditions and keywords).

5 / 5

Trigger Term Quality

Provides good natural keyword coverage ("'long-term memory', 'managed memory', 'memory store', 'agentic memory'" plus "remember a user's…preferences/facts/decisions"), but a few common synonyms a user might say are absent.

4 / 5

Distinctiveness Conflict Risk

Carves a clear niche and explicitly separates it from the self-hosted Lakebase solution (agent-openai-memory / agent-langgraph-memory), minimizing wrong-skill triggering.

5 / 5

Total

18

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (624 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository

databricks/app-templates

Path

agent-openai-agents-sdk-multiagent/.claude/skills/managed-memory/SKILL.md

Reviewed

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