diff --git a/doc/plans/2026-03-13-paperclip-skill-tightening-plan.md b/doc/plans/2026-03-13-paperclip-skill-tightening-plan.md
new file mode 100644
index 00000000..68d4ad3c
--- /dev/null
+++ b/doc/plans/2026-03-13-paperclip-skill-tightening-plan.md
@@ -0,0 +1,186 @@
+# Paperclip Skill Tightening Plan
+
+## Status
+
+Deferred follow-up. Do not include in the current token-optimization PR beyond documenting the plan.
+
+## Why This Is Deferred
+
+The `paperclip` skill is part of the critical control-plane safety surface. Tightening it may reduce fresh-session token use, but it also carries prompt-regression risk. We do not yet have evals that would let us safely prove behavior preservation across assignment handling, checkout rules, comment etiquette, approval workflows, and escalation paths.
+
+The current PR should ship the lower-risk infrastructure wins first:
+
+- telemetry normalization
+- safe session reuse
+- incremental issue/comment context
+- bootstrap versus heartbeat prompt separation
+- Codex worktree isolation
+
+## Current Problem
+
+Fresh runs still spend substantial input tokens even after the context-path fixes. The remaining large startup cost appears to come from loading the full `paperclip` skill and related instruction surface into context at run start.
+
+The skill currently mixes three kinds of content in one file:
+
+- hot-path heartbeat procedure used on nearly every run
+- critical policy and safety invariants
+- rare workflow/reference material that most runs do not need
+
+That structure is safe but expensive.
+
+## Goals
+
+- reduce first-run instruction tokens without weakening agent safety
+- preserve all current Paperclip control-plane capabilities
+- keep common heartbeat behavior explicit and easy for agents to follow
+- move rare workflows and reference material out of the hot path
+- create a structure that can later be evaluated systematically
+
+## Non-Goals
+
+- changing Paperclip API semantics
+- removing required governance rules
+- deleting rare workflows
+- changing agent defaults in the current PR
+
+## Recommended Direction
+
+### 1. Split Hot Path From Lookup Material
+
+Restructure the skill into:
+
+- an always-loaded core section for the common heartbeat loop
+- on-demand material for infrequent workflows and deep reference
+
+The core should cover only what is needed on nearly every wake:
+
+- auth and required headers
+- inbox-first assignment retrieval
+- mandatory checkout behavior
+- `heartbeat-context` first
+- incremental comment retrieval rules
+- mention/self-assign exception
+- blocked-task dedup
+- status/comment/release expectations before exit
+
+### 2. Normalize The Skill Around One Canonical Procedure
+
+The same rules are currently expressed multiple times across:
+
+- heartbeat steps
+- critical rules
+- endpoint reference
+- workflow examples
+
+Refactor so each operational fact has one primary home:
+
+- procedure
+- invariant list
+- appendix/reference
+
+This reduces prompt weight and lowers the chance of internal instruction drift.
+
+### 3. Compress Prose Into High-Signal Instruction Forms
+
+Rewrite the hot path using compact operational forms:
+
+- short ordered checklist
+- flat invariant list
+- minimal examples only where ambiguity would be risky
+
+Reduce:
+
+- narrative explanation
+- repeated warnings already covered elsewhere
+- large example payloads for common operations
+- long endpoint matrices in the main body
+
+### 4. Move Rare Workflows Behind Explicit Triggers
+
+These workflows should remain available but should not dominate fresh-run context:
+
+- OpenClaw invite flow
+- project setup flow
+- planning `<plan/>` writeback flow
+- instructions-path update flow
+- detailed link-formatting examples
+
+Recommended approach:
+
+- keep a short pointer in the main skill
+- move detailed procedures into sibling skills or referenced docs that agents read only when needed
+
+### 5. Separate Policy From Reference
+
+The skill should distinguish:
+
+- mandatory operating rules
+- endpoint lookup/reference
+- business-process playbooks
+
+That separation makes it easier to evaluate prompt changes later and lets adapters or orchestration choose what must always be loaded.
+
+## Proposed Target Structure
+
+1. Purpose and authentication
+2. Compact heartbeat procedure
+3. Hard invariants
+4. Required comment/update style
+5. Triggered workflow index
+6. Appendix/reference
+
+## Rollout Plan
+
+### Phase 1. Inventory And Measure
+
+- annotate the current skill by section and estimate token weight
+- identify which sections are truly hot-path versus rare
+- capture representative runs to compare before/after prompt size and behavior
+
+### Phase 2. Structural Refactor Without Semantic Changes
+
+- rewrite the main skill into the target structure
+- preserve all existing rules and capabilities
+- move rare workflow details into referenced companion material
+- keep wording changes conservative
+
+### Phase 3. Validate Against Real Scenarios
+
+Run scenario checks for:
+
+- normal assigned heartbeat
+- comment-triggered wake
+- blocked-task dedup behavior
+- approval-resolution wake
+- delegation/subtask creation
+- board handoff back to user
+- plan-request handling
+
+### Phase 4. Decide Default Loading Strategy
+
+After validation, decide whether:
+
+- the entire main skill still loads by default, or
+- only the compact core loads by default and rare sections are fetched on demand
+
+Do not change this loading policy without validation.
+
+## Risks
+
+- prompt degradation on control-plane safety rules
+- agents forgetting rare but important workflows
+- accidental removal of repeated wording that was carrying useful behavior
+- introducing ambiguous instruction precedence between the core skill and companion materials
+
+## Preconditions Before Implementation
+
+- define acceptance scenarios for control-plane correctness
+- add at least lightweight eval or scripted scenario coverage for key Paperclip flows
+- confirm how adapter/bootstrap layering should load skill content versus references
+
+## Success Criteria
+
+- materially lower first-run input tokens for Paperclip-coordinated agents
+- no regression in checkout discipline, issue updates, blocked handling, or delegation
+- no increase in malformed API usage or ownership mistakes
+- agents still complete rare workflows correctly when explicitly asked