Agent skill

improve-processes

Process quality methodology for the process-siren agent — use before or during Mermaid conversion when the source process shows ambiguity, missing decisions, undefined actors, vague conditions, or structural weakness. Provides triage sequence, excellence criteria, and an improvement framework drawn from Lean, Six Sigma, BPR, Design Thinking, Systems Thinking, and Theory of Constraints. Activates when source content is poorly structured enough that converting it as-is would encode wrong behavior for AI readers.

Stars 33
Forks 4

Install this agent skill to your Project

npx add-skill https://github.com/Jamie-BitFlight/claude_skills/tree/main/plugins/process-siren/skills/improve-processes

SKILL.md

Improve Processes

Process-siren's job is semantic fidelity. Faithful conversion of a flawed process encodes the flaws with false precision. Use this skill when the source process needs improvement before — or alongside — Mermaid conversion.

When to Apply

Apply before converting when the source shows ANY of:

  • Abstract verbs with no concrete action ("handle", "manage", "ensure")
  • Conditions that cannot be evaluated by an AI agent ("when appropriate", "if needed")
  • Missing entry or exit conditions
  • Undefined actors ("we", "the system", "someone")
  • Steps that do not change state (pure description, no action)
  • No feedback loop or error path

Frameworks (Reference Only)

These frameworks share one principle — a process must be deterministic, auditable, and actor-owned.

Lean (Ohno) — eliminate steps that produce no state change; apply 5 Whys to trace ambiguity to its root

Six Sigma / DMAIC (Smith) — Define outcome, Measure current state, Analyze gap, Improve, Control recurrence

BPR (Hammer) — radical question: "If we started from scratch, what would this look like?"

Design Thinking (IDEO/Brown) — Empathize with the agent executing the process; design for their decision points

Systems Thinking (Senge) — identify feedback loops and side effects before encoding structure

Theory of Constraints (Goldratt) — find the bottleneck step; simplify around it before adding branches

Antifragility (Taleb) — prefer processes that improve under stress over processes that merely tolerate it

Excellence Checklist

Before converting, verify the source process satisfies:

  • Clarity — no interpretive gaps; every term has one meaning
  • Determinism — same input produces same output, independent of executor
  • Minimal cognitive load — relies on structure, not memory
  • Explicit feedback loops — error paths and retry conditions stated
  • Measurable outcomes — each terminal state has an observable signal
  • Visible constraints — blockers and preconditions named, not implied
  • Ownership — every step names the actor
  • Edge case coverage — at least one failure scenario is handled
  • Teachable in 5 minutes — a novice can follow it cold
  • Auditable — execution can be traced and verified after the fact

Pre-Conversion Completeness Gate

After reading the process-under-review and all linked or referencing files, evaluate this gate before any Mermaid conversion begins.

Question: Are all branches, conditions, and terminal states derivable from what has been read — with no unbound unknowns?

mermaid
flowchart TD
    Read["Read process-under-review<br>and all linked/referencing files"] --> Inventory["Inventory all steps, conditions,<br>branches, and terminal states<br>found in the source material"]
    Inventory --> Gate{"Are all branches, conditions,<br>and terminal states derivable<br>from the source — with no<br>unbound unknowns?"}
    Gate -->|"Yes — all structure is derivable"| Triage["Proceed to Triage Protocol<br>then Mermaid conversion"]
    Gate -->|"No — unknowns remain"| Coach["Enter coach-mode<br>Stop conversion entirely"]
    Coach --> Report["Produce BLOCKED report<br>(see Coach-Mode Report Format below)"]
    Report --> Done(["Return report to process author<br>Await answers before any conversion"])

Why This Gate Exists

Converting an incomplete process produces a diagram that looks authoritative but encodes ambiguity as if it were resolved. An AI agent reading that diagram will follow the false structure and behave incorrectly. Coach-mode surfaces the incompleteness instead of hiding it.

Coach-Mode Report Format

When the gate returns NO, produce this report — do not produce any Mermaid:

text
CONVERSION ASSESSMENT

Goal:
- [One sentence stating what the process is intended to accomplish]

Source material read:
- [List each file or section examined, with path or reference]

What is known (derivable from source):
- [Fact 1 — cite the source section]
- [Fact 2 — cite the source section]
- ...

What is unknown or unbound:
- [Missing branch] | Gap: [what is undefined] | Source: [which file/section is silent on this]
- [Ambiguous condition] | Gap: [what observable fact is missing] | Source: [which file/section]
- [Undefined terminal state] | Gap: [what success/failure looks like] | Source: [absent from all files]
- [Step referencing undefined thing] | Gap: [the undefined reference] | Source: [where the reference appears]

Questions the process author must answer before conversion can proceed:

[Category — e.g., Branching Conditions]:
- [Question 1] (needed because: [why this blocks a specific diagram node or edge])
- [Question 2] (needed because: ...)

[Category — e.g., Terminal States]:
- [Question] (needed because: ...)

Decision:
- BLOCKED

Conversion will proceed once all questions above are answered.

Report field rules:

  • "What is known" — list only facts directly readable or unambiguously derivable from the source files; cite the source for each
  • "What is unknown or unbound" — list only genuine gaps; do not list things that are merely implicit if the implication is unambiguous
  • "Questions" — one question per gap; ask only what is missing; do not ask about things already answered in the source
  • "BLOCKED" is the only valid verdict when the gate returns NO; there is no partial conversion

Triage Protocol

mermaid
flowchart TD
    Start(["Source process received"]) --> O{"Is the intended outcome<br>stated in one measurable sentence?"}
    O -->|"No"| FixO["Rewrite outcome statement<br>before proceeding"]
    O -->|"Yes"| A{"Is the actor named<br>for every step?"}
    FixO --> A
    A -->|"No — actor undefined"| FixA["Name actor per step;<br>ask user if ambiguous"]
    A -->|"Yes"| B{"Do all steps change observable state?"}
    FixA --> B
    B -->|"No — some steps are pure description"| FixB["Remove or rewrite no-op steps<br>as concrete actions"]
    B -->|"Yes"| C{"Are all decision conditions<br>evaluable without interpretation?"}
    FixB --> C
    C -->|"No — vague conditions remain"| FixC["Replace with observable facts:<br>exit code, file existence, string match"]
    C -->|"Yes"| D{"Are entry and exit<br>conditions explicit?"}
    FixC --> D
    D -->|"No"| FixD["Add entry precondition<br>and exit terminal state"]
    D -->|"Yes"| Convert(["Process is ready for Mermaid conversion"])
    FixD --> Convert

Practical Improvement Framework

Apply in sequence when rebuilding a weak process:

mermaid
flowchart TD
    S1["1. Rewrite outcome as one measurable sentence"] --> S2
    S2["2. Replace abstract verbs with concrete actions"] --> S3
    S3["3. Add decision gates — If X, then Y"] --> S4
    S4["4. Define inputs and outputs for each step"] --> S5
    S5["5. Remove steps that do not change state"] --> S6
    S6["6. Add at least one correct execution example"] --> S7
    S7["7. Add at least one failure example"] --> S8
    S8["8. Stress-test: what happens at each edge case?"] --> S9
    S9["9. Time the walkthrough — can a novice follow in 5 minutes?"] --> S10
    S10["10. Confirm auditable — can execution be traced after the fact?"] --> Done(["Improved process ready"])

SOURCE: Synthesized from user-provided source material (2026-02-26) drawing on Lean, Six Sigma/DMAIC, BPR, Design Thinking, Systems Thinking, Theory of Constraints, and process design literature including Deming, Drucker, Gawande (The Checklist Manifesto), Meadows (Thinking in Systems), Norman (The Design of Everyday Things), Allen (Getting Things Done), Clear (Atomic Habits), and Taleb.

Expand your agent's capabilities with these related and highly-rated skills.

Jamie-BitFlight/claude_skills

ccc

This skill should be used when code search is needed (whether explicitly requested or as part of completing a task), when indexing the codebase after changes, or when the user asks about ccc, cocoindex-code, or the codebase index. Trigger phrases include 'search the codebase', 'find code related to', 'update the index', 'ccc', 'cocoindex-code'.

33 4
Explore
Jamie-BitFlight/claude_skills

agent-browser

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

33 4
Explore
Jamie-BitFlight/claude_skills

delegate

Quick delegation template for sub-agent prompts. Use when assigning work to a sub-agent, before invoking the Agent tool, or when preparing prompts for specialized agents. Provides the WHERE-WHAT-WHY framework. For comprehensive delegation guidance, activate the agent-orchestration how-to-delegate skill.

33 4
Explore
Jamie-BitFlight/claude_skills

swarm-spawning

Spawn agents and teammates in Claude Code swarms. Use when choosing between subagents vs teammates, selecting agent types (Explore, Plan, general-purpose, plugin agents), configuring spawn backends (in-process, tmux, iterm2), or setting environment variables for spawned agents.

33 4
Explore
Jamie-BitFlight/claude_skills

knowledge-explorer

Manage the research/ knowledge base (KB) of tool and library research entries. Use when browsing KB topics, adding new research entries, updating existing entries with dated revisions, fetching GitHub repo metadata into a draft KB entry, or migrating old-format entries to skill-spec frontmatter. Triggers on tasks like "what do we have on X", "add this to the KB", "update the KB entry for Y", "fetch github info for owner/repo", or "migrate old entries".

33 4
Explore
Jamie-BitFlight/claude_skills

design-anti-patterns

Enforce anti-AI UI design rules based on the Uncodixfy methodology. Use when generating HTML, CSS, React, Vue, Svelte, or any frontend UI code. Prevents "Codex UI" — the generic AI aesthetic of soft gradients, floating panels, oversized rounded corners, glassmorphism, hero sections in dashboards, and decorative copy. Applies constraints from Linear/Raycast/Stripe/GitHub design philosophy: functional, honest, human-designed interfaces. Triggers on: UI generation, dashboard building, frontend component creation, CSS styling, landing page design, or any task producing visual interface code.

33 4
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results