ops(tickets): redmine 490-499 fleshed; session artifacts tracked

logs/q-pdf.log

@@ -4,4 +4,4 @@
   Failed to override models: large model: model "glm-5.2" found in multiple providers: litellm and zai. Please specify
   provider using 'provider/model' format.                                                                             
 
-I have the family patterns. Setting up the task list and starting.
+I have the family patterns. Setting up the task list and starting.Typst stdin→stdout works. Testing image resolution with stdin input:

logs/q-quota.log

@@ -5,4 +5,4 @@ Tickets confirmed. Now researching the z.ai usage API surface.
   Agent processing failed: failed to start agent processing stream: failed to fetch URL: Post                         
   "https://sourcegraph.com/.api/graphql": context deadline exceeded (Client.Timeout exceeded while awaiting headers). 
 
-Codebase understood. Now researching the z.ai usage endpoint.Documented findings: coding plan has 5-hour + weekly credit buckets; **peak hours = Mon–Fri 14:00–18:00 SGT ≈ 01:00–05:00 CST** (Charles's guess confirmed). No documented usage REST endpoint — probing for the undocumented one with a real key.Gateway responds under `/api/coding/*` but no public usage route. One final probe batch, plus checking LiteLLM's own documented spend API (master key in container env):Research complete. Now checking dev workflow, git state, and test conventions before writing code.All context gathered. Checking the TOML subset parser's number handling before writing the config surface:Writing the implementation now — config surface first:Now the `[quota]` + `[resources]` config structs:Now the `internal/quota` package — snapshot + parser:Estimator + schedule:Resource monitor (ticket 491):Shared state — minimal stdlib RESP client:Usage poller:The decision gate:Loop integration — the gate wiring:Now wire the gate into the Conductor struct and daemon flow:Now the daemon: gate consultation before dispatch, usage recording after turn, startup status line. Also state.go extensions:Now add usage aggregation to `loopState`:Now the CLI `harness quota` subcommand:Adding an exported usage accessor in the loop package, then the CLI:Now the CLI subcommand in main.go:Now the test suite — quota package first:Resources + fake-redis tests:Config load test + loop integration tests:Extend the fakeRedmine fixture with per-issue classes:
+Codebase understood. Now researching the z.ai usage endpoint.Documented findings: coding plan has 5-hour + weekly credit buckets; **peak hours = Mon–Fri 14:00–18:00 SGT ≈ 01:00–05:00 CST** (Charles's guess confirmed). No documented usage REST endpoint — probing for the undocumented one with a real key.Gateway responds under `/api/coding/*` but no public usage route. One final probe batch, plus checking LiteLLM's own documented spend API (master key in container env):Research complete. Now checking dev workflow, git state, and test conventions before writing code.All context gathered. Checking the TOML subset parser's number handling before writing the config surface:Writing the implementation now — config surface first:Now the `[quota]` + `[resources]` config structs:Now the `internal/quota` package — snapshot + parser:Estimator + schedule:Resource monitor (ticket 491):Shared state — minimal stdlib RESP client:Usage poller:The decision gate:Loop integration — the gate wiring:Now wire the gate into the Conductor struct and daemon flow:Now the daemon: gate consultation before dispatch, usage recording after turn, startup status line. Also state.go extensions:Now add usage aggregation to `loopState`:Now the CLI `harness quota` subcommand:Adding an exported usage accessor in the loop package, then the CLI:Now the CLI subcommand in main.go:Now the test suite — quota package first:Resources + fake-redis tests:Config load test + loop integration tests:Extend the fakeRedmine fixture with per-issue classes:First build pass to catch compile errors: