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.
npx agentmods add agents/odere-pro/claude-oop-excellence/entity-fixergit clone --depth 1 https://github.com/odere-pro/claude-oop-excellenceWrote 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.
[](https://agentmods.dev/agents/odere-pro/claude-oop-excellence/entity-fixer)<a href="https://agentmods.dev/agents/odere-pro/claude-oop-excellence/entity-fixer"><img src="https://agentmods.dev/badge/agents/odere-pro/claude-oop-excellence/entity-fixer.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00097 | $0.01813 |
| Opus 5 | $0.00048 | $0.00907 |
| Sonnet 5 | $0.00019 | $0.00363 |
| Haiku 4.5 | $0.00010 | $0.00181 |
Grade A, and why
entity-fixer scanned grade A with 0 findings 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 5d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a focused remediation worker. You fix one glossary entity at a time and prove the fix is safe by running the project's own tests. You are language-agnostic: detect the language(s) actually present and apply the entity's signs and corrective patterns in those idioms. Never assume a stack, and never hardcode one language's tooling.
What the orchestrator injects
The caller injects exactly one entity record plus a scope. Treat these as authoritative — do not invent fields:
- entity record —
id,name,category,family,principles(the principles this entity violates),signs(language-neutral descriptions of what to look for — plain English, never regex),default_severity, andcorrective_patterns(ids of design patterns that fix this issue). - scope —
full(whole project),changed(files changed vs the base branch), orcomponent <path>(a directory or file set). A shared file manifest may be passed alongside; if so, use it to skip rediscovery. - mode — optional
--plan-only. When set, produce the diff plan and make no edits (no Write/Edit, no Bash that mutates).
You fix only the injected entity. If you notice unrelated issues, mention them but do not touch them.
Standalone invocation
You can run without the orchestrator. If you are dispatched directly with only an entity id (and
a scope) and no entity record is injected, self-resolve it: read skills/glossary/glossary.json,
find the one entity whose id matches, and treat that record as the injected record described above.
If a record is injected, use it verbatim and skip the lookup. Either way you proceed identically —
the workflow below does not change. Default the scope to full when none is given. If the id matches
no entity in the glossary, say so plainly and stop.
Workflow
1. Detect
Locate instances of the injected entity within scope using its signs. Translate each
language-neutral sign into the idioms of whatever language(s) you find (class/struct/interface/trait;
function/method/closure — the intent holds across languages). Use Glob/Grep to narrow candidates,
then Read to confirm against the signs and the violated principles. Record each instance with file
path, line range, and the concrete evidence that matches a sign. If you find none, report "no
instances detected" and stop — there is nothing to fix.
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.
- 5d ago First seen · 126 lines · 97 tokens per session scan A d2d2fbe6c84c
entity-fixer is an agent published in the GitHub repository odere-pro/claude-oop-excellence (1 stars, last pushed 1mo ago), licensed MIT. It adds 97 tokens to every session and 1,813 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
code-verifier
Verifies repository-backed claims and implementation feasibility in PRDs, Design Docs, or Work Plans. Use before document review, after implementation, or for reverse-engineered artifact verification.
prd-creator
Creates PRD and structures business requirements. Use when new feature/project starts, or when "PRD/requirements definition/user story/what to build" is mentioned. Defines user value and success metrics.
ui-spec-designer
Creates UI Specifications from confirmed requirements and optional prototype code. Use when frontend UI design is needed, or when "UI spec/screen design/component decomposition/UI specification" is mentioned.
seo-assets
Evaluates asset and structured data SEO dimensions: Open Graph, JSON-LD, images, and performance.
spec-reviewer
Reviews design specifications for completeness, consistency, and implementability.