retrospective-eval

name	retrospective-eval
description	Retrospective evaluation of engram observations — rate global usefulness and project relevance to improve memory quality over time

Retrospective Evaluation Skill

Purpose

Evaluate the usefulness of observations that were recently injected into your context. This creates a feedback loop: observations you find helpful get boosted; irrelevant ones get demoted or suppressed.

When to Use

• Periodically (daily/weekly) to review recent observations
• After a session where injected context was particularly helpful or unhelpful
• When explicitly asked to evaluate memory quality

Process

Step 1: Get Recent Observations

Fetch observations to evaluate. Choose one source:

Option A — From injected context: Review the <engram-context> block in your current session. These are the observations that were injected for you.

Option B — From API (broader review):

GET /api/observations/recently-injected?limit=20&project={current_project}

or

GET /api/observations/top?limit=20&project={current_project}

Step 2: Evaluate Each Observation

For each observation, assess TWO dimensions:

Dimension	Scale	Question
Global Usefulness	0-10	Is this observation universally valuable across ALL projects?
Project Relevance	0-10	Is this observation relevant to the CURRENT project?

Step 3: Map Verdicts to Actions

Global	Project	Verdict	Action
>= 7	any	keep(global)	Set scope=global, boost importance
< 7	>= 7	keep(project)	Keep scope=project, boost importance
3-6	3-6	demote	Lower importance score
< 3	< 3	suppress	Mark as suppressed (excluded from injection)

Step 4: Apply Actions via MCP Tools

For each verdict, use only currently advertised engram tools. The significance tool is conditional; if it is absent, report the rating as unavailable instead of calling a retired alias.

Boost (keep), when rate_memory_significance is advertised:

rate_memory_significance(id=<observation_id>, rating="useful")

Demote, when rate_memory_significance is advertised:

rate_memory_significance(id=<observation_id>, rating="not_useful")

Suppress:

feedback(action="suppress", id=<observation_id>)

Step 5: Report Summary

Output a table of evaluations:

| ID | Title | Type | Global | Project | Verdict |
|----|-------|------|--------|---------|---------|
| 123 | Auth middleware pattern | decision | 8 | 9 | keep(global) |
| 456 | npm install completion | discovery | 1 | 1 | suppress |
| 789 | Redis cache config | bugfix | 5 | 7 | keep(project) |

Evaluation Guidelines

High global usefulness (7-10):

• Architecture decisions that affect multiple projects
• Security patterns and gotchas
• Cross-project conventions and standards
• Bug patterns that recur across codebases

High project relevance (7-10):

• Project-specific decisions and trade-offs
• Bug fixes in the current codebase
• Configuration choices for this project
• Domain-specific patterns

Low value (0-3) — candidates for suppression:

• Tool discovery mechanics ("ToolSearch Query Pattern")
• Generic status transitions
• Error messages from other projects
• Trivially re-discoverable facts
• Observations about tools that are always available

Notes

• Do NOT evaluate observations from the current session (too fresh)
• Focus on observations older than 1 day for meaningful assessment
• If unsure, default to demote rather than suppress (suppression is harder to undo)
• Run this evaluation weekly for best results