Make the company legible to AI: structured knowledge, decision principles, customer insight, industry know-how, process rules, and capability assets.
If knowledge is not recorded, classified, reviewed, and callable, it cannot become part of the company's intelligence system.
Important meetings, customer signals, delivery lessons, and decision logic must enter structured records.
Every useful context item needs capture, storage, retrieval, feedback, and update paths.
Tools change quickly. Business judgment, customer insight, and operating know-how compound over time.
Service definitions, delivery standards, pricing logic, cooperation model, and technology choices.
Customer selection, project trade-offs, brand tone, risk boundary, and escalation rules.
Customer profiles, demand patterns, sales objections, conversion signals, and success factors.
Trends, competitors, compliance signals, policy changes, and technology evolution.
Delivery workflows, collaboration standards, quality control, and communication SOPs.
Agent configuration, workflow templates, toolchain patterns, and evaluation benchmarks.
Every context record needs enough metadata for humans and Agents to understand source, permission, freshness, confidence, and applicability.
| Field group | Required fields | Purpose |
|---|---|---|
| Identity | context_id, category, title, summary, content | Make the record unique, readable, and independently understandable. |
| Retrieval | tags, related_entities, applicable_scenarios, source | Help Agents find the right context and understand where it came from. |
| Governance | confidence, access_level, owner, review_cycle | Control use in high-risk situations and assign responsibility. |
| Lifecycle | created_at, updated_at, next_review, version, quality_score, usage_count | Keep context fresh, traceable, and measurable. |
| Scenario | Captured content | Method | Category |
|---|---|---|---|
| Customer communication | Meetings, demand, feedback | Transcription and structured summary | CI |
| Project delivery | Deliverables, acceptance, review | Project-system archive | CI + BK |
| Agent execution | Task log, success, failure, time cost | Automatic runtime records | SA |
| Sales process | Questions, objections, win/loss causes | CRM and conversation extraction | CI + DP |
| Industry monitoring | News, policy, competitors | Scheduled monitoring and summary | IK |
| Internal collaboration | Decisions, problem solving, knowledge sharing | Collaboration record archive | DP + PR |
| Website and content | Content publishing, behavior data, GEO performance | Analytics collection | BK + IK |
Required fields are complete and the content includes enough examples or data.
The record is inside its review cycle and still matches current business conditions.
Agents can use the context directly without needing hidden explanation.
Claims are verified by practice, source quality, or multiple independent signals.
| Grade | Score | Use policy |
|---|---|---|
| A | 18-20 | Agents can use it autonomously in approved scenarios. |
| B | 14-17 | Usable, but high-risk use needs human confirmation. |
| C | 10-13 | Reference only; confidence must be shown. |
| D | 6-9 | Improve in the next review cycle or archive. |
| F | 4-5 | Deprecated and blocked from Agent use. |
Acquisition, consulting, GEO, delivery, knowledge, quality, and monitoring Agents.
Semantic retrieval, exact structured search, and knowledge-graph traversal.
Six categories, permission levels, lifecycle state, and quality scoring.
Shared business knowledge, industry know-how, public decision principles, and reusable assets.
Customer-specific information, proposal details, communication records, and pricing context.
Private notes, early ideas, and sensitive drafts that can later be promoted when ready.
A good context system helps Agents answer, decide, and escalate with the right business boundaries.
Discuss context design