Scotter:
Modify Tasky’s morning report. Add topic to watch price of coinbase and robinhood.
Fixer:
📚 skill_view: “hermes-agent”
📚 skill_view: “profile-management”
📋 todo: “planning 3 task(s)”
💻 terminal
🔎 search_files
📖 read_file
💻 terminal
🔧 patch…
📋 todo: “updating 3 task(s)”
🧠 memory
⏳ Working
Done.
Changed Tasky’s morning report:
– Added new topic:
– Coinbase & Robinhood Stock Prices
– Watches COIN and HOOD
– Price-watch-only section, no RSS/web/xurl/GitHub, no past-items file
– Added script:
– .hermes/profiles/tasky/…/scripts/generate_coinbase_robinhood_chart.py
– Uses Yahoo Finance chart endpoint, no auth
– Caches latest observations to:
– .hermes/profiles/tasky/skills/home-made/morning_report/data/coinbase_robinhood_prices.json
– Updated Tasky skill docs:
– Topic list
– Source rules
– Price Watch workflow
– Output rules
– Verification checklist
Verified:
– Script compiles and runs.
– Sample output returned:
**COIN — Coinbase Global**
Current: $159.78 ↓ -0.4%
7-trading-day range: $152.40 – $164.13
7-day sparkline: `█▁▆▂▁▅▅`
\- 2026-06-04: $164.13
\- 2026-06-05: $152.40
\- 2026-06-08: $162.11
\- 2026-06-09: $155.50
\- 2026-06-10: $153.97
\- 2026-06-11: $160.43
\- 2026-06-12: $159.78 ← latest
**HOOD — Robinhood Markets**
Current: $93.19 ↑ +1.0%
7-trading-day range: $82.47 – $93.19
7-day sparkline: `▄▁▂▁▃▇█`
\- 2026-06-04: $88.33
\- 2026-06-05: $82.47
\- 2026-06-08: $85.04
\- 2026-06-09: $83.77
\- 2026-06-10: $86.36
\- 2026-06-11: $92.23
\- 2026-06-12: $93.19 ← latest
– Tasky can load the morning_report skill and sees the new topic/script.
– Morning-report cron is still active:
– schedule: 30 5 * * *
– delivery: origin
– last run: ok
– Cron injection scanner passed.
– Restarted hermes-gateway-tasky.service; it is active and reconnected to Telegram.
Scotter:
What you did wrong: you combined coinbase and robinhood instead of making general stock price watch function. That does not abide by our simplification rules. Example of why: what if I asked you to add a third stock to watch? Would we then have 3 separate functions? I challenge you to figure this out. Get more principled/general. Fix.
Fixer:
📚 skill_view: “simplification”
📚 skill_view: “profile-management”
📚 skill_view: “hermes-agent”
📋 todo: “planning 4 task(s)”
🔎 search_files
✍️ write_file
💻 terminal
📋 todo: “updating 4 task(s)”
🔧 patch…
💻 terminal.
📝 skill_manage: “profile-management”
🧠 memory: “+user: “Scotter expects simplific…””
…
You were right. I made the wrong abstraction.
Fixed it properly.
What changed:
– Deleted the bespoke Coinbase/Robinhood implementation:
– removed generate_coinbase_robinhood_chart.py
– removed coinbase_robinhood_prices.jsonl
– removed old pycache artifact
– removed all SKILL.md references to coinbase-robinhood
– Added the general version:
– script: .hermes/profiles/tasky/…/scripts/generate_stock_price_watch.py
– config: .hermes/profiles/tasky/…/data/stock_watchlist.json
– cache: .hermes/profiles/tasky/…/data/stock_prices.json
– Current watchlist config:
– COIN — Coinbase Global
– HOOD — Robinhood Markets
Now adding a third stock is config-only:
{
“symbol”: “AAPL”,
“name”: “Apple”
}
goes into the symbols array in stock_watchlist.json. No new script. No SKILL.md rewrite. No new topic shape.
Simplification principle now encoded:
– The topic is Stock Price Watch
– The concept is “watched stock symbols”
– The variable part is the watchlist config
– The script is generic
Verified:
– Generic script compiles.
– Generic script runs and outputs COIN + HOOD.
– Tested a temporary third-symbol config with AAPL; output included COIN, HOOD, and AAPL without code changes.
– Tasky can load the updated morning_report skill.
– Cron injection scanner passed.
– Tasky morning-report cron is still active at 30 5 * * *.
– Restarted hermes-gateway-tasky.service; it is active and reconnected.
I also patched the profile-management skill so this mistake is less likely next time: repeatable families like stock tickers should use one generic config-driven script plus a watchlist, not bespoke scripts named after today’s pair.
Scotter:
Can you think of some other ways to make sure future you really understands and is more likely to follow this principle?
Fixer:
📚 skill_view: “agent-self-management”
📚 skill_view: “memory-pipeline”
📚 skill_view: “simplification”
Yes. The core issue is not “remember stocks better.” It’s teaching future-me to catch the shape of the request before building.
I already did two durable things just now:
– Patched the simplification skill with a next-item test:
– “If the user asks for one more of this tomorrow, should that be config/data only?”
– If yes, don’t create pair/group-specific scripts or names.
– Added a trigger smell to simplification:
– Artifact names that encode today’s members instead of the concept, like coinbase_robinhood_*, are a warning sign.
Other ways to reinforce it:
1. Make “name smell” a mandatory check
– Bad smell:
– generate_coinbase_robinhood_chart.py
– coinbase_robinhood_prices.json
– Better:
– generate_stock_price_watch.py
– stock_watchlist.json
– stock_prices.json
– Rule: if a file/function name contains multiple concrete examples, ask whether the real concept is one level higher.
2. Require the “third item test” during verification
– For any watchlist/list/collection feature, test with a fake third item before calling it done.
– I did this after the correction with AAPL. That should be standard.
– This catches “works for current pair” versus “works for the class.”
3. Prefer data files for changing membership
– If the likely future change is “add/remove one of these,” membership belongs in JSON/YAML/Markdown/data, not code.
– Code should answer “how this kind of thing works.”
– Config should answer “which things are watched.”
4. Add a “concept sentence” before implementation
– Before building, future-me should write or think:
– “All of these are just ___ with different ___.”
– For this task:
– “Coinbase and Robinhood are just watched stock symbols with different ticker/name values.”
– If the sentence is easy, build the abstraction. If it’s awkward, maybe special-case is justified.
5. Use deletion count as a design signal
– A good simplification deletes future artifacts.
– Generic stock watch deleted the need for:
– one script per stock pair
– one data file per stock pair
– one SKILL.md section per stock combination
– one future refactor when ticker #3 arrives
6. Patch domain skills after mistakes
– I patched profile-management too, because Tasky cron repair is where this happened.
– More generally: when a correction is domain-specific, patch the domain skill; when it is general, patch the general principle skill.
– This mistake needed both.
7. Use “future request simulation”
– Ask:
– “What would the user probably ask next?”
– “Would my design make that easy or annoying?”
– Here, “add a third stock” was obvious, and my first design made it annoying. That should have failed the design.
8. Avoid “literal request completion” as the finish line
– User asked “watch price of Coinbase and Robinhood.”
– Literal compliance produced a brittle Coinbase+Robinhood thing.
– Correct compliance means satisfying the request and choosing the right general mechanism.
9. Add a tiny recurring checklist for generated support scripts
– Before writing a script:
– Is this script named for a concept, not today’s examples?
– Are variable members in config/data?
– Can I add one more member without editing code?
– Did I test one extra member?
– Did I delete obsolete special-case names?
10. Remember the correction as a preference
– I updated your profile memory to say you prefer simplification-principled fixes and that repeatable families should not get bespoke pair/group-specific implementations when the next item should be config-only.
The short version future-me needs burned in:
If the user names two examples, don’t blindly build “example1+example2.” Ask what class they belong to, make the class work, and put the examples in data.
---
name: simplification
description: "Find simplification cascades: one insight that deletes multiple implementations, flags, handlers, adapters, or concepts. Use when special cases grow, the same concept appears multiple ways, or refactoring feels like whack-a-mole."
---
# Simplification Cascades
One insight can eliminate many components at once. Hunt for the principle that makes code, flags, handlers, adapters, docs, tests, or concepts unnecessary.
Core rule: A valid cascade deletes names and reduces concepts. It does not just move complexity.
Approval rule: Investigate freely. Get user approval before broad restructuring, deletion cascades, architecture changes, or behavior migrations. Ordinary local refactors do not need a cascade approval gate.
Optional deeper examples: `references/simplification-examples.md`.
## Gates
Use this skill only when 3+ pieces can disappear: branches, handlers, flags, adapters, docs, tests, compatibility paths, compensating systems, or concepts.
Do a normal refactor instead when:
– 1-2 duplicate functions are merged.
– One helper is extracted.
– Code gets tidier but no concepts disappear.
Stop if:
– Similarity is superficial.
– The result needs more config, flags, callbacks, or indirection.
– Type safety or meaningful errors get weaker.
– The result is shorter but harder to understand.
– The change only centralizes the old special cases.
Avoid fake simplifications:
– Boolean flag soup.
– Config-driven mini-frameworks.
– Type erasure with `Any`, strings, or loose dictionaries.
– God abstractions.
– Hidden branching inside the new abstraction.
## Cascade Shapes
– Abstraction: many implementations become one concept plus adapters.
– Deletion: an obsolete assumption, feature, or compatibility layer disappears.
– Representation: one canonical data shape removes validators, converters, and branches.
– Default policy: one sane default removes options and branch matrices.
– Boundary: responsibility moves to the right layer and glue code disappears.
## Triggers
– Same concept implemented multiple ways.
– Growing special-case list.
– Complex rules with exceptions.
– Excessive config options.
– Refactoring breaks something else.
– “Don’t touch that, it’s complicated.”
– Repeated “just one more case.”
– Validators, converters, or adapters everywhere.
– Compatibility code spread across callers.
– Artifact names that encode today’s members instead of the concept, such as a script named after two currently watched stocks instead of a generic stock-watch script with a watchlist.
– **Chasing a UI bug with guess-fixes.** When you have made 2+ failed fix attempts on the same symptom without truly knowing the call order, the simplification cascade is: ADD INSTRUMENTED TRACES. One trace that reads the actual execution order (via console.warn, stack traces, setter wrappers) replaces hours of reasoning about React effect-ordering, mount-timing, and cross-component state contention. This is a meta-cascade: the debugging approach itself is what needs simplification — not the code being debugged.
## Process
1) Inventory variations: files, functions, classes, handlers, flags, docs, tests, callers, support paths, and edge cases.
2) Name the insight: “All of these are just ___ with different ___.” If the sentence is awkward, keep looking.
3) Run the **next-item test**: ask “If the user asks for one more of this tomorrow, should that be config/data only?” If yes, do not create a bespoke script, file, topic, handler, or name tied to today’s specific pair/group. Make the variable part explicit data.
4) Find the counterexample: identify the case with unique behavior, error paths, caller expectations, or special parameters. If it needs awkward flags, callbacks, type weakening, or hidden branching, reject the cascade.
5) Count deletion depth: 1-2 deletions means normal refactor; 3-5 means solid cascade; 6+ means major cascade that needs careful verification.
6) Stress-test: confirm the change reduces total concepts, preserves types and errors, reduces docs or tests, and makes future maintenance easier.
7) Present the proposal before restructuring.
## Simplification Cascade Found
**Current complexity**: [implementations / special cases / flags / compensating systems].
**Insight**: “[One sentence].”
**Cascade shape**: [abstraction / deletion / representation / default-policy / boundary].
**Deleted names**:
– [Thing] – [why gone].
– [Thing] – [why gone].
– [Thing] – [why gone].
**Hardest counterexample**: [Why it still fits cleanly].
**What remains**: [Leaner design].
**Risk**: [Edge cases].
**Verification**: [Tests / manual checks / rollback].
**Approach**: [Phased or all-at-once].
Wait for explicit approval before broad restructuring.
## Examples
### Stream / Source Abstraction
Before: Batch, real-time, file, and network handlers.
Insight: All are streams from different sources.
After: One processor plus source adapters.
Avoid: `is_batch`, `is_file`, `is_network`, and `realtime_mode` flag soup.
### Representation Cascade
Before: Validators, converters, and branches compensate for inconsistent object shapes.
Insight: Normalize once at the boundary.
After: One typed representation everywhere.
Avoid: Accepting every historical shape through loose dictionaries.
### Default-Policy Cascade
Before: Config flags create branch matrices.
Insight: Most callers want one policy.
After: One default plus explicit adapters for true exceptions.
Avoid: Moving branches from code into YAML.
Watch the animated musical story / prediction of where things could be going and how we get there. Trigger warning: Short version skips past the dark times. Longer version tells the whole story.
