docs: ROADMAP eval metrics ideas and eval README runtime invariants

ROADMAP.md: add eval harness performance metrics section (raw metrics,
per-test scores, comparison matrix, benchmark targets); reformat
Application API interface list as sub-items under the config note.

eval/README.md: add Runtime Invariants section documenting always-on
behaviors (memory, meta tools, single profile); update architecture
listing to include all current case files; reflow long prose lines.

ROADMAP.md

@@ -228,9 +228,18 @@ flowchart LR
 
 ## Ideas and improvements
 
+- [ ] Add performance metrics to the eval harness
+  - [ ] Raw metrics of tool calls, LLM calls, token counts, duration, etc
+  - [ ] Per-test scores
+  - [ ] Side-by-side comparison matrix
+  - [ ] Compare to other agent runtimes
+  - [ ] Compare to upstream origin picoclaw
+  - [ ] What benchmarks should we be running?
+  - [ ] What are the key performance metrics we should be tracking?
 - [ ] Add a new tool for the agent to use: `focus_search`
 - [ ] Clean up the main.go and extract to modules
 - [ ] Create a pure Application API that I/O calls into
+  - [ ] all of these should be able to be configured and plugged in/out at runtime
     - [ ] cli
     - [ ] daemon
     - [ ] web
@@ -244,7 +253,6 @@ flowchart LR
     - [ ] spi
     - [ ] pwm
     - [ ] etc
-  - [ ] all of these should be able to be configured and plugged in/out at runtime
 - [ ] Migrate to Cobra CLI framework
   - [ ] Use command-palette pattern for subcommands
   - [ ] keep cli commands as pure cli that calls into the application

eval/README.md

@@ -21,6 +21,14 @@ make eval-test
 make eval-compare
 ```
 
+## Runtime Invariants
+
+The current agent architecture has these always-on behaviors:
+
+- Memory is always enabled.
+- Meta tools are always registered (`tool_search`, `tool_call`).
+- Eval runs against a single runtime profile via `eval/bin/eval-runner`.
+
 ## Architecture
 
 ```
@@ -30,7 +38,13 @@ eval/
 │   ├── tool_calling.yaml
 │   ├── token_efficiency.yaml
 │   ├── multi_step.yaml
-│   └── edge_cases.yaml
+│   ├── edge_cases.yaml
+│   ├── memory_ops.yaml
+│   ├── meta_tools.yaml
+│   ├── skills.yaml
+│   ├── subagent.yaml
+│   ├── reasoning.yaml
+│   └── error_recovery.yaml
 ├── go_evals/            # Go-native component tests (memory, tools)
 ├── scripts/             # CI/comparison scripts
 │   └── compare.sh
@@ -41,11 +55,9 @@ eval/
 
 ## How It Works
 
-1. **eval-runner** wraps picoclaw with an instrumented language model that captures
-   every LLM call, tool invocation, token count, and timing.
+1. **eval-runner** wraps picoclaw with an instrumented language model that captures every LLM call, tool invocation, token count, and timing.
 
-2. **promptfoo** invokes `eval-runner` via `exec:` provider, sending prompts as JSON
-   on stdin and parsing the structured trace JSON from stdout.
+2. **promptfoo** invokes `eval-runner` via `exec:` provider, sending prompts as JSON on stdin and parsing the structured trace JSON from stdout.
 
 3. **Assertions** are JavaScript functions that inspect the trace to score:
    - Tool selection correctness
@@ -98,9 +110,7 @@ Create a new YAML file in `eval/cases/` following this pattern:
 
 ## A/B Comparison
 
-`make eval-compare` builds both your current branch and main, then runs the
-identical test suite against both. Results show a side-by-side comparison
-matrix with per-test scores.
+`make eval-compare` builds both your current branch and main, then runs the identical test suite against both. Results show a side-by-side comparison matrix with per-test scores.
 
 ## Environment Variables