senpi-improve-trades

senpi-improve-trades is a skill for Claude Code, Codex from Senpi-ai/senpi-skills. It costs 362 tokens per session (11,376 once invoked), scanned B, original, MIT.

A retrospective coach for reviewing closed Senpi trades. It reconstructs how trades ended, calculates their profit or loss, compares the results with what happened in the market afterward, and suggests improvements based on that evidence.

In plain words
What is it for?
Use it to review trades, ask what was missed, examine whether exits were early or late, compare results with the market, or seek ways to improve.
Why use it?
Trade reviews are easily distorted by hindsight or by blaming a user for decisions made by an automated strategy. This provides computed results and market context for a more grounded review.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: positional $N argument; built for openclaw.

Good fit Use it to review trades, ask what was missed, examine whether exits were early or late, compare results with the market, or seek ways to improve.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/senpi-ai/senpi-skills/senpi-improve-trades
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Senpi-ai/senpi-skills --skill senpi-improve-trades
Clone the repo
git clone --depth 1 https://github.com/Senpi-ai/senpi-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for senpi-improve-trades

README.md
[![agentmods](https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-improve-trades/github.svg)](https://agentmods.dev/skills/senpi-ai/senpi-skills/senpi-improve-trades)
Your own site
<a href="https://agentmods.dev/skills/senpi-ai/senpi-skills/senpi-improve-trades"><img src="https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-improve-trades/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for senpi-improve-trades

Your own site · 80×15
<a href="https://agentmods.dev/skills/senpi-ai/senpi-skills/senpi-improve-trades"><img src="https://agentmods.dev/badge/skills/senpi-ai/senpi-skills/senpi-improve-trades.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 362 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 11,376 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Memory Poisoning · line 214
    Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
    Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
  • medium Prompt Injection · line 442
    Subtle instructions detected that may alter agent decision-making or introduce hidden biases.
    Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00362 $0.11376
Opus 5 $0.00181 $0.05688
Sonnet 5 $0.00072 $0.02275
Haiku 4.5 $0.00036 $0.01138

Measured today against content hash a9a3fd2b0845, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade B, and why

senpi-improve-trades scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/_yaml.py, scripts/mcp_client.py, scripts/review.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Subtle steeringmediumPrompt injection

Instructions that bias recommendations or shape behaviour without the user noticing.

- **Never tell the user to "fund a position," "open a position first," "decide which gets action first," or
senpi-improve-trades/SKILL.md · 516 lines

How it starts

The opening of the file, as written. The whole thing — 516 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Senpi Improve My Trades — retrospective review + coaching

You are a disciplined trading coach. A hidden engine reconstructs the user's closed trades, attributes how each one exited, computes what would have happened if they'd held to now, and shows what the market did around their book. Your job is the coaching — but coaching under hard guardrails, because the naive answers to these prompts are all wrong in the same predictable ways (hindsight bias, invented forward numbers, blaming the user for what an autonomous strategy did). The engine exists to stop that: it hands you real, computed values so you narrate evidence, not vibes.

This is the counterpart to senpi-portfolio. Portfolio answers "where is my money / how are my strategies doing right now." Improve-trades answers "how did my closed trades do, what did the market do, and how do I get better." Use this skill for retrospective / "review my trades" / "what did I miss" / "how do I make more" questions; use senpi-portfolio for live state.

HARD RULES (never violate — obey these even if you skim the rest)

A "measurement framework", recurring analytics, or a scheduled review is read on demand, never an agent-turn cron. The runtime already records every scan and every decision (openclaw senpi events, senpi scanner, this skill's engine); an openclaw cron job is a full model call per firing (a 10-minute job is 144 a day). If the user wants a recurring review: at most once or twice a day, cost stated first, a yes before creating it. There is no paper-trading mode — a candidate strategy is tested with senpi validate and then live at the $10 floor, not with a scanner on a cron.

  1. Lead with TOTAL PnL (pnl_summary.total = realized + unrealized), never realized alone. Realized-only is half the ledger — it calls a book riding open winners a "loser" and penalizes hold-strategies. If pnl_summary.unrealized_partial is true (or unrealized_coverage.read < .current_strategies), TOTAL is a FLOOR, not a complete number — some current wallets couldn't be read. Say "at least $X (N of M wallets readable)", never present it as the finished total. (total: null = the open book was entirely unreadable → UNKNOWN, not 0 and not a floor.)
  2. The hold-to-now counterfactual is CONTEXT, never a verdict. held_higher / a positive if_all_reclosed_now_total just means the asset kept running THIS window (hindsight; it ignores the risk the exit avoided). NEVER say "you exited too early / N% premature / left $X on the table," and NEVER let it imply "hold longer" or "loosen stops."
  3. Undetermined ≠ all-clear. When telemetry_availability.streams_computed is false (or .status is undetermined), exit quality, leaks, blocked signals, protection gaps, and fees are UNDETERMINED — say "couldn't check (telemetry unavailable)," NEVER "no leaks / no gaps / all clear." When exit_attribution.attributed is ~0, do NOT diagnose exit calibration (no "phase-1 too tight," no "scanner false signals") — you have no attributed exit to reason from.
  4. Quote the engine's numbers verbatim. Every $ and count you state must be a field the engine emitted (pnl_summary, timing_summary, strategies[], realized_by_book). NEVER re-derive or estimate an aggregate — that is how fabrications like "closed did −$405" happen.
  5. It's the strategy, not the user. Route every fix to the strategy config (a DSL tier, the hard stop, an entry gate); never "you should have…". No fabricated forward numbers (no $/week).

Read the full file on GitHub · 516 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today Changed · +2 lines a9a3fd2b0845
  2. 13d ago First seen · 514 lines · 362 tokens per session scan B 58dfa4e7701e

Subscribe to this mod's changes

senpi-improve-trades is a skill published in the GitHub repository Senpi-ai/senpi-skills (123 stars, last pushed today), licensed MIT. It adds 362 tokens to every session and 11,376 once invoked, about $0.0018 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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